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Tukova, Sarka. "Adaptive mesh storm surge modelling". Thesis, University of Oxford, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.542983.
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Brown, Martin. "Neurofuzzy adaptive modelling and control". Thesis, University of Southampton, 1993. https://eprints.soton.ac.uk/250157/.
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The drive for autonomy in manufacturing is making increasing demands on control systems, both for improved performance and for extra flexibility. This is reflected in the research and development of autonomously guided vehicles which must operate safely in ill-defined, complex and time-varying environments. Traditional control systems generally make infeasible assumptions which limit their application within this domain, and therefore current research has concentrated on Intelligent Control techniques in order to make the control systems flexible and robust. An integral part of intelligence is the ability to learn from a systems interaction with its environment, and this thesis provides a unified description of several adaptive neural and fuzzy networks. The recent resurgence of interest in these two anthropomorphic techniques has seen these algorithms widely applied within learning control systems, although a firm theoretical framework which can compare different networks and establish convergence and stability conditions has not evolved. Such results are essential if these adaptive algorithms are to be used in real-world applications where safety and correctness are prime concerns. The work described in this thesis addresses these questions by introducing a class of systems called associative memory networks, which is used to describe the similarities and differences which exist between certain fuzzy and neural algorithms. All of the networks can be implemented within a 3-layer structure, where the output is linearly dependent on a set of adjustable parameters. This allows parameter convergence to be established when a gradient descent training rule is used, and the rate of convergence can be directly related to the condition of the network's basis functions. The size, shape and position of these basis functions gives each network its own specific modelling attributes, since the learning rules are identical. Therefore it is important to study the network's internal representation as this provides information about how each network generalises (both interpolation and extrapolation), the rate of parameter convergence and the type of nonlinear functions which can be successfully modelled. Three networks are described in detail: the Albus CMAC, the is given of the Albus CMAC which illustrates its desirable features for on-line, nonlinear adaptive modelling and control: local learning and a computational cost which depends linearly on the input space dimension. The modelling capabilities of the algorithm are rigorously analysed and it is shown that they are strongly dependent on the generalisation parameter, and a set of consistency equations is derived which specify how the network generalises. The adaptive B-spline network, which embodies a piecewise polynomial representation, is also described and used for nonlinear modelling and constructing a static rule base which guides and autonomous vehicle into a parking slot. B-splines are also used for on-line, constrained trajectory generation where they approximate a set of velocity or positional subgoals. Fuzzy systems are typically ill-defined, although the approach taken in this thesis is to use algebraic rather than truncation operators and smooth fuzzy sets which means that the modelling capabilities of the fuzzy network can be determined exactly, and convergence and stability results can be derived for these algorithms. These results focus research on the learning, modelling and representational abilities of the networks by providing a common framework for their analysis. The desirable features of the networks (local learning, linearly dependent on the parameter set, fuzzy interpretation) are emphasised, and the algorithms are all evaluated on a common time series prediciton problem.
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Kemppainen, A. (Anssi). "Adaptive methods for autonomous environmental modelling". Doctoral thesis, Oulun yliopisto, 2018. http://urn.fi/urn:isbn:9789526218519.
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Abstract In this thesis, we consider autonomous environmental modelling, where robotic sensing platforms are utilized in environmental surveying. In order to allow a wide range of different environments, our models must be flexible to the data with some a prior assumptions. Respectively, in order to guide action planning, we need to have a unified sensing quality metric that depends on the prediction quality of our models. Finally, in order to be able to adapt to the observed information, at each iteration of the action planning algorithm, we must be able to provide solutions that aim at minimum travelling time needed to reach a certain level of sensing quality. These are the main topics in this thesis. At the center of our approaches are stationary and non-stationary Gaussian processes based on the assumption that the observed phenomenon is due to the diffusion of white noise, where diffusion kernel anisotropy and scale may vary between locations. For these models, we propose adaptation of diffusion kernels based on a structure tensor approach. Proposed methods are demonstrated with experiments that show, assuming sensor noise is not dominating, our iterative approach is able to return diffusion kernel values close to correct ones. In order to quantify how precise our models are, we propose a mutual information based sensing quality criterion, and prove that the optimal design using our sensing quality provides the best prediction quality for the model. To incorporate localization uncertainty in modelling, we also propose an approach where a posterior model is marginalized over sensing path distribution. The benefit is that this approach implicitly favors actions that result in previously visited or otherwise well-defined areas, meanwhile, maximizing the information gain. Experiments support our claims that our proposed approaches are best when considering predictive distribution quality. In action planning, our approach is to use graph-based approximation algorithms to obtain a certain level of model quality in an efficient way. In order account for spatial dependency and active localization, we propose adaptation methods that map sensing quality to vertex prices in a graph. Experiments demonstrate the benefit of our adaptation methods compared to the action planning algorithms that do not consider these specific featuresTiivistelmä Tässä väitöskirjassa tarkastellaan autonomista ympäristön mallinnusta, missä ympäristön kartoitukseen hyödynnetään robottimittausalustoja. Erilaisia ympäristöjä varten, käytettävien mallien tulee olla joustavia datalle tietyillä a priori oletuksilla. Mittausalustojen ohjaus vaatii vastaavasti yhtenäisen, mallien ennustuslaadusta riippuvan, kartoituksen laatumetriikan. Mukautuakseen uuteen informaatioon, ohjausalgoritmin tulee lisäksi pyrkiä joka iteraatiolla minimoimaan tietyn kartoituksen laadun saavuttava kulkuaika. Nämä ovat tämän väitöskirjan pääaiheet. Tämän väitöskirjan keskiössä ovat sellaiset stationaariset ja ei-stationaariset Gaussin prosessit, jotka perustuvat oletukseen että havaittu ilmiö johtuu valkoisen kohinan diffuusiosta. Diffuusiokernelin anisotrooppisuudelle ja skaalalle sallitaan paikkariippuvaisuus. Tässä väitöskirjassa esitetään näiden mallien mukauttamiseen rakennetensoripohjaisia menetelmiä. Suoritetut kokeet osoittavat, että esitetyt iteratiiviset mukauttamismenetelmät tuottavat lähes oikeita diffuusiokernelien arvoja, olettaen, että sensorikohina ei dominoi mittauksia. Mallien ennustustarkkuuden määrittämiseen esitetään keskinäisinformaatioon perustuva kartoituksen laatumetriikka. Väitöskirjassa todistetaan, että optimaalinen ennustuslaatu saavutetaan käyttämällä esitettyä laatumetriikkaa. Väitöskirjassa esitetään lisäksi laatumetriikka, jossa posteriori malli on marginalisoitu kartoituspolkujen jakauman yli. Tämän avulla voidaan huomioida paikannusepävarmuuden vaikutukset mallinnuksessa. Tällöin etuna on se, että kyseinen laatumetriikka suosii implisiittisesti sellaisia mittausalustojen ohjauksia, jotka johtavat aeimmin kartoitetuille tai helposti ennustettaville alueille samalla maksimoiden informaatiohyödyn. Suoritetut kokeet tukevat väittämiä, että väitöskirjassa esitetyt menetelmät tuottavat parhaan ennustusjakauman laadun. Mittausalustojen ohjaus vaatii vastaavasti yhtenäisen, mallien ennustuslaadusta riippuvan, kartoituksen laatumetriikan. Väitöskirjassa esitetään mukautusmenetelmiä kartoituksen laadun kuvaukseksi graafin solmujen kustannuksiksi. Tämän avulla sallitaan sekä spatiaalinen riippuvuus että aktiivinen paikannus. Mittausalustojen ohjaus vaatii vastaavasti yhtenäisen, mallien ennustuslaadusta riippuvan, kartoituksen laatumetriikan
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Albakour, M.-Dyaa. "Adaptive domain modelling for information retrieval". Thesis, University of Essex, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.573703.
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Moore, Gareth Lewis. "Adaptive statistical class-based language modelling". Thesis, University of Cambridge, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.620315.
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Adam, Alexandros. "Finite element, adaptive spectral wave modelling". Thesis, Imperial College London, 2016. http://hdl.handle.net/10044/1/45307.
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The ability to predict the wave climate has a great impact on a wide range of sectors, including coastal and offshore engineering, marine renewable energy and shipping. The state of the art in wave prediction is called spectral wave modelling and is based on a phase-averaged, spectral description of the sea-surface elevation. The governing equation, called the action balance equation, is five-dimensional and describes the generation, propagation and evolution of action density in geographic space, spectral space and time. Due to the multidimensional nature of the equation the feasible resolutions are restricted by the computational costs. The aim of this work is to propose schemes which can increase the range of possible resolutions in spectral wave modelling, with the use of adaptivity in space and angle. Thus, this work focuses on the development of an unstructured, adaptive finite element spectral wave model (Fluidity-SW). A sub-grid scale model for the spatial discretisation is used, which retains the stability of discontinuous systems, with continuous degrees of freedom. Then, a new framework for angular adaptivity is developed, with results in dynamic angular and spatial anisotropy of the angular mesh. Finally a spatially h−adaptive scheme is implemented, which can dynamically treat the spatial gradients of the solution fields. The resulting framework is thoroughly verified and validated in a wide range of test cases and realistic scenarios, against analytical solutions, wave measurements and the results obtained with the widely used SWAN model. Thus, the overall ability of the code to simulate surface gravity wind-waves in fixed and adaptive spatial and angular meshes is demonstrated.
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Sani, Yusuf. "Advanced modelling of adaptive bitrate selection". Thesis, Lancaster University, 2017. http://eprints.lancs.ac.uk/88536/.
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Nowadays, a typical video content provider serves a variety of platforms e.g. smartphones, web browsers, and smart TVs. Each of these platforms has specific requirements with respect to transmission and video quality. Moreover, since these devices are increasingly being used on-the-go, the environment within which most of these video streaming clients operate is both unreliable and time-varying. To cater for these heterogeneous requirements, content providers are increasingly adopting adaptive streaming services. Through such services, the quality of the video content received by a user is adapted to fit its specific requirements and capabilities. To adapt the video quality, system capabilities such as network capacity and memory have to be continuously monitored and measured, chunk requests have to be scheduled, and then the optimal video rate has to be decided. Each of these tasks is usually managed by a sub-module of the adaptive bitrate selection function. However, these sub-components interact in a non-trivial manner. For example, while on-off chunk scheduling helps to prevent buffer overflow, it negatively affects the TCP throughput. Hence, these complex interactions between these different sub-components of the adaptive streaming algorithm result in unnecessary rebufferings, undesirable variability, and sub-optimal video quality. To help simplify these interactions, this thesis develops several frameworks and models that define the relationships between the various components of the adaptive bitrate selection system. This includes deriving the valid system state space, which defines the state that an algorithm can be in at any given time, determining the allowable interactions between the various components, and identifying the video quality evolution rules that optimise QoE. Using this information, some state-of-the-art algorithms are improved and novel ones developed to demonstrate the effectiveness of the proposed approach. The result of extensive evaluations conducted both within a real-world Internet environment and with network trace shows the proposed schemes help in reducing the convergence time, startup delay, and rebuffering events, while at the same time increasing both the average and the stability of the video quality. All this is obtained without any adverse impact on the fairness among the competing players.
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Rojas, Durán Gonzalo Eduardo. "Modelling adaptive web applications in OOWS". Doctoral thesis, Universitat Politècnica de València, 2008. http://hdl.handle.net/10251/2000.
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Las Aplicaciones Web Adaptativas son sistemas Web que plantean una solución a esta problemática, mediante la adaptación automática del acceso a ítems de información, servicios e hiperlinks, en base a las características de los usuarios. El desarrollo de estos sistemas exige adoptar una aproximación ingenieril que facilite la especificación de las funcionalidades adaptativas a proveer, junto con las características de los usuarios en las cuales se basan dichas funcionalidades.
La presente tesis introduce una aproximación al desarrollo de Aplicaciones Web Adaptativas desde una perspectiva dirigida por modelos. Esta aproximación integra prácticas tradicionales de desarrollo de Aplicaciones Web con conceptos de-nidos y probados por la comunidad de Hipermedia Adaptativa. Tomando como base el proceso de desarrollo de aplicaciones Web OOWS (Object Oriented Web Solutions), se defíne un conjunto de primitivas
conceptuales que permiten expresar técnicas adaptativas a un alto nivel de abstracción. La definición de estas primitivas es respaldada por una propuesta de Modelado de Usuarios. Además, un conjunto de estrategias de modelado
permite incorporar Métodos Adaptativos a los esquemas navegacionales de OOWS, en base a dichas primitivas.Rojas Durán, GE. (2008). Modelling adaptive web applications in OOWS [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/2000
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Wilson, Troy Daniel. "Adaptive Sampling For Efficient Online Modelling". Thesis, The University of Sydney, 2017. http://hdl.handle.net/2123/17257.
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This thesis examines methods enabling autonomous systems to make active sampling and planning decisions in real time. Gaussian Process (GP) regression is chosen as a framework for its non-parametric approach allowing flexibility in unknown environments. The first part of the thesis focuses on depth constrained full coverage bathymetric surveys in unknown environments. Algorithms are developed to find and follow a depth contour, modelled with a GP, and produce a depth constrained boundary. An extension to the Boustrophedon Cellular Decomposition, Discrete Monotone Polygonal Partitioning is developed allowing efficient planning for coverage within this boundary. Efficient computational methods such as incremental Cholesky updates are implemented to allow online Hyper Parameter optimisation and fitting of the GP's. This is demonstrated in simulation and the field on a platform built for the purpose. The second part of this thesis focuses on modelling the surface salinity profiles of estuarine tidal fronts. The standard GP model assumes evenly distributed noise, which does not always hold. This can be handled with Heteroscedastic noise. An efficient new method, Parametric Heteroscedastic Gaussian Process regression, is proposed. This is applied to active sample selection on stationary fronts and adaptive planning on moving fronts where a number of information theoretic methods are compared. The use of a mean function is shown to increase the accuracy of predictions whilst reducing optimisation time. These algorithms are validated in simulation. Algorithmic development is focused on efficient methods allowing deployment on platforms with constrained computational resources. Whilst the application of this thesis is Autonomous Surface Vessels, it is hoped the issues discussed and solutions provided have relevance to other applications in robotics and wider fields such as spatial statistics and machine learning in general.
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Deshmukh, Pushkaraj M. "Modelling error estimation and adaptive modelling of functionally graded materials". Cincinnati, Ohio : University of Cincinnati, 2004. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=ucin1096036755.
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Muñoz, Novoa David. "Adaptive urban modelling for solar energy simulations". Doctoral thesis, Universitat de Girona, 2019. http://hdl.handle.net/10803/668194.
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In summary, this thesis proposes to address the problem of simulating physical effects in large urban environments through the use of procedural rules and Level-of-Detail techniques, in order to reduce the computational complexity of these simulations, but at the same time trying to maintain an acceptable accuracy in the results for decision-making. The final results show that it is possible to obtain credible results in different study cases, all with reasonable calculation times, with the user being able to adjust the parameters to obtain the desired balance between accuracy and calculation time.En resum, aquesta tesi proposa abordar el problema de simular els efectes físics en grans entorns urbans mitjançant l'ús de regles procedimentals i tècniques de nivell de detall, per tal de reduir la complexitat computacional d'aquestes simulacions, però tractant alhora de mantenir una precisió acceptable en els resultats per a la presa de decisions. Els resultats finals mostren que és possible obtenir resultats creïbles en diferents casos d'estudi, tots amb temps de càlcul raonables, amb l'usuari ajustant els paràmetres per obtenir l'equilibri desitjat entre precisió i temps de càlcul.
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Moakes, Paul Alan. "On-line adaptive nonlinear modelling of speech". Thesis, University of Sheffield, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.364189.
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Morris, Paul John. "Modelling peatlands as a complex adaptive systems". Thesis, Queen Mary, University of London, 2010. http://qmro.qmul.ac.uk/xmlui/handle/123456789/479.
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A new conceptual approach to modelling peatlands, DigiBog, involves a Complex Adaptive Systems consideration of raised bogs. A new computer hydrological model is presented, tested, and its capabilities in simulating hydrological behaviour in a real bog demonstrated. The hydrological model, while effective as a stand-alone modelling tool, provides a conceptual and algorithmic structure for ecohydrological models presented later. Using DigiBog architecture to build a cellular model of peatland patterning dynamics, various rulesets were experimented with to assess their effectiveness in predicting patterns. Contrary to findings by previous authors, the ponding model did not predict patterns under steady hydrological conditions. None of the rulesets presented offered an improvement over the existing nutrient-scarcity model. Sixteen shallow peat cores from a Swedish raised bog were analysed to investigate the relationship between cumulative peat decomposition and hydraulic conductivity, a relationship previously neglected in models of peatland patterning and peat accumulation. A multivariate analysis showed depth to be a stronger control on hydraulic conductivity than cumulative decomposition, reflecting the role of compression in closing pore spaces. The data proved to be largely unsuitable for parameterising models of peatland dynamics, due mainly to problems in core selection. However, the work showed that hydraulic conductivity could be expressed quantitatively as a function of other physical variables such as depth and cumulative decomposition. DigiBog architecture was used to build a simple, vertical, ecohydrological model of long-term peat accumulation. As model complexity was increased under a self-organisation approach, model predictions of peat accumulation rates and surface wetness changed dramatically, revealing the importance of feedbacks between peatland hydrological behaviour and peat physical properties. This work may have important implications for palaeoclimatic reconstructions which assume peatland surface wetness to be a reliable climatic indicator. The expansion of the model to include horizontal space altered model behaviour in quantitative and qualitative terms.
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Hutchison, Andrew. "Modelling adaptive routing in Wide Area Networks". Master's thesis, University of Cape Town, 1991. http://hdl.handle.net/11427/13555.
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Bibliography: leaves 132-138.This study investigates the modelling of adative routing algorithms with specific reference to the algorithm of an existing Wide Area Network (WAN). Packets in the network are routed at each node on the basis of routing tables which contain internal and external delays for each route from the node. The internal delay on a route represents the time that packets queued for transmission will have to wait before being transmitted, while the external delay on a route represents the delay to other nodes via that route. Several modelling methods are investigated and compared for the purpose of identifying the most appropriate and applicable technique. A model of routing in the WAN using an analytic technique is described. The hypothesis of this study is that dynamic routing can be modelled as a sequence of models exhibiting fixed routing. The modelling rationale is that a series of analytic models is run and solved. The routing algorithm of the WAN studied is such that, if viewed at any time instant, the network is one with static routing and no buffer overflow. This characteristic, together with a real time modelling requirement, influences the modelling technique which is applied. Each model represents a routing update interval and a multiclass open queueing network is used to solve the model during a particular interval. Descriptions of the design and implementation of X wan, an X Window based modelling system, are provided. A feature of the modelling system is that it provides a Graphical User Interface (GUI), allowing interactive network specification and the direct observation of network routing through the medium of this interface. Various applications of the modelling system are presented, and overall network behaviour is examined. Experimentation with the routing algorithm is conducted, and (tentative) recommendations are made on ways in which network performance could be improved. A different routing algorithm is also implemented, for the purpose of comparison and to demonstrate the ease with which this can be affected.
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Czarkowski, Marek. "A scrutable adaptive hypertext". Thesis, The University of Sydney, 2006. http://hdl.handle.net/2123/10206.
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Fuelled by the popularity and uptake of the World Wide Web since the 1990s, many researchers and commercial vendors have focussed on Adaptive Hypermedia Systems as an effective mechanism for disseminating personalised information and services. Such systems store information about the user, such as their goals, interests and background, and use this to provide a personalised response to the user. This technology has been applied to a number of contexts such as education systems, e-commerce applications, information search and retrieval systems. As an increasing number of systems collect and store personal information about their users to provide a personalised service, legislation around the world increasingly requires that users have access to view and modify their personal data. The spirit of such legislation is that the user should be able to understand how personal information about them is used. There literature has reported benefits of allowing users to access and understand data collected about them, particularly in the context of supporting learning through reflection. Although researchers have experimented with open user models, typically the personalisation is inscrutable: the user has little or no visibility in to the adaptation process. When the adaptation produces unexpected results, the user may be left confused with no mechanism for understanding why the system did what it did or how to correct it. This thesis is the next step, giving users the ability to see what has been personalised and why. In the context of personalised hypermedia, this thesis describes the first research to go beyond open, or even scrutable user models; it makes the adaptivity and associated processes open to the user and controllable. The novelty of this work is that a user of an adaptive hypertext system might ask How was this page personalised to me? and is able to see just how their user model affected what they saw in the hypertext document. With an understanding of the personalisation process and the ability to control it, the user is able to steer the personalisation to suit their changing needs, and help improve the accuracy of the user model. Developing an interface to support the scrutinisation of an adaptive hypertext is difficult. Users may not scrutinise often as it is a distraction from their main task. But when users need to scrutinise, perhaps to correct a system misconception, they need to easily find and access the scrutinisation tools. Ideally, the tools should not require any training and users should be able to use them effectively without prior experience or if have not used them for a long time, since this is how users are likely to scrutinise in practice. The contributions of thesis are: (1) SASY/ATML, a domain independent, reusable framework for creation and delivery of scrutable adaptive hypertext; (2)a toolkit of graphical tools that allow the user to scrutinise, or inspect and understand what personalisation occurred and control it; (3) evaluation of the scrutinisation tools and (4) a set of guidelines for providing support for the scrutinisation of an adaptive hypertext through the exploration of several forms of scrutinisation tools.
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Tariq, Imran. "Adaptive modelling of tumour volume dynamics under radiotherapy". Thesis, University of Surrey, 2016. http://epubs.surrey.ac.uk/811035/.
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The focus of this research was to apply mathematical and computational methods for modelling and prediction of tumour volume during the course of radiotherapy. The developed tools could provide valuable information for the optimisation of radiotherapy in the future. Firstly, the feasibility of modelling tumour volume dynamics of individual patients, as measured by computed tomography (CT) imaging, was explored. The main objective was to develop a model that is adequate to describe tumour volume dynamics, and at the same time is not excessively complex as lacking support from clinical data. To this end, various modelling options were explored, and rigorous statistical methods, the Akaike information criterion (AIC) and the corrected Akaike information criterion (AICc), were used for model selection. The models were calibrated to data from two cohorts of non-small cell lung cancer patients, one treated by stereotactic ablative radiotherapy and the other by conventionally fractionated radiotherapy. The results showed that a two-population model with exponential tumour growth is the most appropriate for the data studied as judged by AIC and AICc. Secondly, this model was further equipped with a Bayesian adaption approach in order to predict individual patients’ response to radiotherapy in terms of tumour volume change during the treatment. The main idea was to start from a population-average model, which is subsequently updated, using Bayesian parameter estimation, from an individual’s tumour volume measurement. Therefore the model becomes more and more personalised and so is the prediction. The usefulness of the developed method was demonstrated on clinical data. Finally, attempt was made to link the predicted tumour volume (an important but often secondary treatment outcome indicator) to tumour control probability (one of the primary indicators of treatment outcome), and this model was demonstrated through a simulation study. Overall this research has contributed new methods and results of mathematical modelling for quantitatively analysis and prediction of individual patients’ response to radiotherapy; it represents a significant development that could be used for improved and personalised planning and scheduling of radiotherapy in the future.
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Ultes, Stefan [Verfasser]. "User-centred adaptive spoken dialogue modelling / Stefan Ultes". Ulm : Universität Ulm, 2015. http://d-nb.info/1122195621/34.
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Cao, Jiangtao. "Modelling and adaptive control of vehicle suspension systems". Thesis, University of Portsmouth, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.500329.
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Vehicle suspension systems, as one kind of typical non-linear systems, play a crucial role in riding comfort, safety handling, and road damage minimization in modern vehicles. Three contributions have been made in this thesis in response to the problems raised from vehicle non-linear and uncertain properties. A novel framework of type-2 fuzzy control system for vehicle active suspensions has been constructed with emphasizes on its mathematical vehicle modelling and control.
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Kochenderfer, Mykel J. "Adaptive modelling and planning for learning intelligent behaviour". Thesis, University of Edinburgh, 2006. http://hdl.handle.net/1842/1408.
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An intelligent agent must be capable of using its past experience to develop an understanding of how its actions affect the world in which it is situated. Given some objective, the agent must be able to effectively use its understanding of the world to produce a plan that is robust to the uncertainty present in the world. This thesis presents a novel computational framework called the Adaptive Modelling and Planning System (AMPS) that aims to meet these requirements for intelligence. The challenge of the agent is to use its experience in the world to generate a model. In problems with large state and action spaces, the agent can generalise from limited experience by grouping together similar states and actions, effectively partitioning the state and action spaces into finite sets of regions. This process is called abstraction. Several different abstraction approaches have been proposed in the literature, but the existing algorithms have many limitations. They generally only increase resolution, require a large amount of data before changing the abstraction, do not generalise over actions, and are computationally expensive. AMPS aims to solve these problems using a new kind of approach. AMPS splits and merges existing regions in its abstraction according to a set of heuristics. The system introduces splits using a mechanism related to supervised learning and is defined in a general way, allowing AMPS to leverage a wide variety of representations. The system merges existing regions when an analysis of the current plan indicates that doing so could be useful. Because several different regions may require revision at any given time, AMPS prioritises revision to best utilise whatever computational resources are available. Changes in the abstraction lead to changes in the model, requiring changes to the plan. AMPS prioritises the planning process, and when the agent has time, it replans in high-priority regions. This thesis demonstrates the flexibility and strength of this approach in learning intelligent behaviour from limited experience.
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Sienz, J. "Integrated structural modelling, adaptive analysis and shape optimization". Thesis, Swansea University, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.639033.
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The present work is concerned with the development of procedures for an integrated system for computer aided structural optimization including topology optimization, image processing and shape optimization for two dimensional structures. At the beginning, such a system is introduced. This system integrates aspects of design and analysis modelling, behaviour sensitivity analysis, optimization and creative control via interactive graphics. A satisfactory solution of structural optimization problems can only be achieved by having a profound knowledge of each of these aspects. The introduction of an integrated system for structural optimization is followed by the establishment of a pool of blocks to build such a system. Firstly, a flexible shape definition tool for two dimensional structures using B-splines is shown. This is followed by an adaptive, automatic mesh generator for unstructured meshes consisting of triangular or quadrilateral meshes which allows to generate full FE problem definitions. The FE analysis is carried out using this input for plane stress/plane strain problems, solids of revolution and for engineering problems governed by the Helmholtz equations. The accuracy of the FE analysis is improved by applying adaptive refinement methods in combination with the Zienkiewicz-Zhu error estimator and nodal averaging or the SPR method to compute nodal stresses. For shape optimization, the behaviour sensitivities of the structure are computed using semi-analytical methods (exact or conventional) or the global finite difference method. The optimization is carried out using mathematical programs which are used as black boxes. These tools are then combined to build two applications for integrated structural optimization.
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Wong, Lawrence Yik-Lung. "Adaptive system modelling for active attenuation of sound". Thesis, Open University, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.316967.
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Maddison, James R. "Adaptive mesh modelling of the thermally driven annulus". Thesis, University of Oxford, 2011. http://ora.ox.ac.uk/objects/uuid:4b95031b-4517-4aaf-9bb2-4d6d4a145499.
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Numerical simulations of atmospheric and oceanic flows are fundamentally limited by a lack of model resolution. This thesis describes the application of unstructured mesh finite element methods to geophysical fluid dynamics simulations. These methods permit the mesh resolution to be concentrated in regions of relatively increased dynamical importance. Dynamic mesh adaptivity can further be used to maintain an optimised mesh even as the flow develops. Hence unstructured dynamic mesh adaptive methods have the potential to enable efficient simulations of high Reynolds number flows in complex geometries. In this thesis, the thermally driven rotating annulus is used to test these numerical methods. This system is a classic laboratory scale analogue for large scale geophysical flows. The thermally driven rotating annulus has a long history of experimental and numerical research, and hence it is ideally suited for the validation of new numerical methods. For geophysical systems there is a leading order balance between the Coriolis and buoyancy accelerations and the pressure gradient acceleration: geostrophic and hydrostatic balance. It is essential that any numerical model for these systems is able to represent these balances accurately. In this thesis a balanced pressure decomposition method is described, whereby the pressure is decomposed into a ``balanced'' component associated with the Coriolis and buoyancy accelerations, and a ``residual'' component associated with other forcings and that enforces incompressibility. It is demonstrated that this method can be used to enable a more accurate representation of geostrophic and hydrostatic balance in finite element modelling. Furthermore, when applying dynamic mesh adaptivity, there is a further potential for imbalance injection by the mesh optimisation procedure. This issue is tested in the context of shallow-water ocean modelling. For the linearised system on an $f$-plane, and with a steady balance permitting numerical discretisation, an interpolant is formulated that guarantees that a steady and balanced state remains steady and in balance after interpolation onto an arbitrary target mesh. The application of unstructured dynamic mesh adaptive methods to the thermally driven rotating annulus is presented. Fixed structured mesh finite element simulations are conducted, and compared against a finite difference model and against experiment. Further dynamic mesh adaptive simulations are then conducted, and compared against the structured mesh simulations. These tests are used to identify weaknesses in the application of dynamic mesh adaptivity to geophysical systems. The simulations are extended to a more challenging system: the thermally driven rotating annulus at high Taylor number and with sloping base and lid topography. Analysis of the high Taylor number simulations reveals a direct energy transfer from the eddies to the mean flow, confirming the results of previous experimental work.
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Gonçalves, Diogo Antunes. "Energy management systems based on adaptive surrogate modelling". Doctoral thesis, Universidade de Aveiro, 2017. http://hdl.handle.net/10773/23559.
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Doutoramento em Sistemas Energéticos e Alterações ClimáticasEstima-se que o sector dos edifícios seja responsável por cerca de 40% da totalidade de energia consumida na União Europeia e Estados Unidos da América. 50% dessa energia está alocada a sistemas de aquecimento, ventilação e ar-condicionado (AVAC), dos quais 20% estimam-se ser desperdiçados devido a ineficiência na gestão de energia. Considera-se pertinente focar-se no melhoramento da eficiência energética do edificado, reduzindo o desperdício de forma a evitar a escassez de recursos fósseis, bem como para mitigar os problemas ambientais e as alterações climáticas causadas pelo consumo e produção de energia. A tese propõe abordagens e metodologias que permitem tomar o controlo preditivo de supervisão dos sistemas de climatização enquanto medida de reabilitação energética na requalificação de edifícios. A principal contribuição deste trabalho prende-se com a implementação e desenvolvimento de metamodelos adaptativos baseados em aprendizagem computacional que assistam o processo de otimização multi-objetivo inerente ao controlo supervisor da gestão de energia em edifícios de serviços. Esta metodologia deverá ainda permitir a sua implementação de forma agnóstica a natureza dos sistemas AVAC existentes no edifício. A metodologia apresentada propõe uma abordagem convergente com o estado da arte no desenvolvimento científico na área da inteligência artificial. O esforço mínimo requerido para a implementação deste tipo de sistema de gestão inteligente e avaliado, concluindo-se que o seu potencial de aplicação e significativo. Para este fim, foi desenvolvida uma aplicação informática capaz de conduzir toda a metodologia em regime de simulação computacional de modo a averiguar a utilidade das soluções propostas pelo sistema de controlo supervisor desenvolvido. Os resultados obtidos apresentam soluções compatíveis com o melhoramento do paradigma energético-ambiental corrente, contribuindo desse modo para uma maior sustentabilidade do edificado obsoleto em termos energéticos. Os custos com energia alocada a sistemas AVAC podem alcançar uma redução de 27% dos custos base, acompanhando uma melhoria ao nível do conforto dos ocupantes. Mesmo em casos em que a requalificação da envolvente do edifício e do sistema de climatização seja anterior a implementação de um sistema de gestão inteligente, ou que a envolvente seja já competente em termos de eficiência energética (como o caso de estudo apresentado), a poupança energética e, ainda assim, assegurada devido a natureza flexível e autodidata do sistema de supervisão proposto. Portanto, recomenda-se que a reabilitação energética de edifícios tome como prioridade a requalificação do sistema de controlo AVAC por sistemas avançados e supervisores de controlo de forma a potenciarem a inércia dos edifícios, bem como toda a informação disponível na atual era digital.
Buildings account for almost 40% of the total energy consumption in the European Union and the United States combined. From that fraction, 50% is allocated to the heating, ventilation and air-conditioning systems (HVAC), from which 20% is wasted due to system's ine ciency. Considering that most of this energy is obtained from scarce fossil reserves and its consumption has an adverse impact on the climate change problem, it is of utmost importance to reduce energy wastes, namely by improving the overall energy e ciency of buildings. This thesis postulates the implementation of intelligent supervisory control systems for new or existing HVAC equipment as an energy retro tting measure concurrent with conventional architectural and systems retro tting. The proposed methodology is characterized by a exible, yet robust predictive control algorithm, capable of supervising generic HVAC systems in real-time by suggesting high-level controls, resulting in an optimized compromise between occupants' comfort requirements and energy consumption (and/or cost), taking advantage of the building constructive characteristics and information availability. The proposed solution integrates the exibility of machine learning techniques with the robustness of surrogate models to deliver data-driven predictive models capable of assisting the multi-objective optimization problem of minimizing energy consumption and cost while improving occupants comfort. The proposed modelling and optimization strategies are presented as a novelty capable of answering the quest for a robust yet exible supervisory predictive control for generic HVAC systems. A software package capable of delivering advanced and generic supervisory predictive controls, especially focusing on the scope of building energy retro tting was developed and used as the delivery method for the results presented in this thesis. The obtained results suggest that o ce buildings, characterized by a contemporary construction and HVAC system, can be improved regarding overall energy e ciency and occupants comfort by retro tting the control solution adding a supervisory predictive control level, external to the existing HVAC system. The expected energy saving by considering the proposed control are in line with the requirements imposed by the present energy and climate change framework, with up to 27% savings of energy related costs due to autonomous demand shifting. Moreover, it is recommended that building energy retro ts should consider as a priority the update of the energy control strategies by adding supervisory solutions capable of capitalizing the use of the building thermal inertia as well as the available data in this current information era (occupancy schedules, weather, etc.).
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Bai, Jiongjun. "Adaptive hidden Markov noise modelling for speech enhancement". Thesis, Imperial College London, 2013. http://hdl.handle.net/10044/1/11158.
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A robust and reliable noise estimation algorithm is required in many speech enhancement systems. The aim of this thesis is to propose and evaluate a robust noise estimation algorithm for highly non-stationary noisy environments. In this work, we model the non-stationary noise using a set of discrete states with each state representing a distinct noise power spectrum. In this approach, the state sequence over time is conveniently represented by a Hidden Markov Model (HMM). In this thesis, we first present an online HMM re-estimation framework that models time-varying noise using a Hidden Markov Model and tracks changes in noise characteristics by a sequential model update procedure that tracks the noise characteristics during the absence of speech. In addition the algorithm will when necessary create new model states to represent novel noise spectra and will merge existing states that have similar characteristics. We then extend our work in robust noise estimation during speech activity by incorporating a speech model into our existing noise model. The noise characteristics within each state are updated based on a speech presence probability which is derived from a modified Minima controlled recursive averaging method. We have demonstrated the effectiveness of our noise HMM in tracking both stationary and highly non-stationary noise, and shown that it gives improved performance over other conventional noise estimation methods when it is incorporated into a standard speech enhancement algorithm.
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Liu, Xiaoming. "Towards a unified modelling framework for adaptive networks". University of the Western Cape, 2014. http://hdl.handle.net/11394/4466.
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Philosophiae Doctor - PhDAdaptive networks are complex networks with nontrivial topological features and connection patterns between their elements which are neither purely regular nor purely random. Their applications are in sociology, biology, physics, genetics, epidemiology, chemistry, ecology, materials science, the traditional Internet and the emerging Internet of-Things. For example, their applications in sociology include social networks such as Facebook which have recently raised the interest of the research community. These networks may hide patterns which, when revealed, can be of great interest in many practical applications. While the current adaptive network models remain mostly theoretical and conceptual, however, there is currently no unified modelling framework for implementing the development, comparison, communication and validation of agent-based adaptive network models through using proper empirical data and computation models from different research fields. In this thesis, a unified framework has been developed that combines agent- based adaptive network models and adaptive control structures. In this framework, the control parameters of adaptive network models are included as a part of the state- topology coevolution and are automatically adjusted according to the observations obtained from the system being studied. This allows the automatic generation of enhanced adaptive networks by systematically adjusting both the network topology and the control parameters at the same time to accurately reflect the real-world complex system. We develop three different applications within the general framework for agent- based adaptive network modelling and simulation of real-world complex systems in different research fields. First, a unified framework which combines adaptive net- work models and adaptive control structures is proposed for modelling and simulation of fractured-rock aquifer systems. Moreover, we use this unified modelling framework to develop an automatic modelling tool, Fracture3D, for automatically building enhanced fracture adaptive network models of fractured-rock aquifer systems, in which the fracture statistics and the structural properties can both follow the observed statistics from natural fracture networks. We show that the coupling between the fracture adaptive network models and the adaptive control structures with iterative parameter identification can drive the network topology towards a desired state by dynamically updating the geometrical states of fractures with a proper adaptive control structure. Second, we develop a unified framework which combines adaptive network models and multiple model adaptive control structures for modelling and simulation of social network systems. By using such a unified modelling framework, an automatic modelling tool, SMRI, is developed for automatically building the enhanced social adaptive network models through using mobile-phone-centric multimodal data with suitable computational models of behavioural state update and social interaction update. We show that the coupling between the social adaptive network models and the multiple model adaptive control structures can drive the community structure of a social adaptive network models towards a desired state through using the suitable computational models of behavioural state update and social interaction update predetermined by the multiple model adaptive control structure. Third, we develop a unified framework which combines adaptive network models and support vector machine based adaptive control structures for modelling and simulation of multicast congestion in mobile ad hoc network systems. Moreover, a multicast congestion detection scheme, WMCD, has been developed for the unified modelling framework, in which the incipient congestions of group members can be predicted by using support vector machine-based prediction models and current traffic states. We show that the network’s throughput capacity is efficiently improved through using the unified modelling framework, which dynamically adjusting the group structures according to the updated congestion states of group members generated by the WMCD scheme in order to relieve the high load.
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Wilson, Cian. "Modelling multiple-material flows on adaptive unstructured meshes". Thesis, Imperial College London, 2009. http://hdl.handle.net/10044/1/5526.
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The ability to distinguish between regions with different material properties is essential when numerically modelling many physical systems. Using a dual control volume mesh that avoids the problem of corner coupling, the HyperC face value scheme is extended to multiple dimensions and applied as a device for material advection on unstructured simplex meshes. The new scheme performs well at maintaining sharp interfaces between materials and is shown to produce small advection errors, comparable to those of standard material advection methods on structured meshes. To further minimise numerical diffusion of material interfaces a total variation bounded flux limiter, UltraC, is defined using a normalised variable diagram. Combining the material tracking scheme with dynamically adapting meshes, the use of a minimally dissipative bounded projection algorithm for interpolating fields from the old mesh to the new, optimised mesh is demonstrated that conserves the mass of each material. More generally, material conservation during the advection process is ensured through the coupling of the material tracking scheme to the momentum and mass equations. A new element pair for the discretisation of velocity and pressure is proposed that maintains the stability of the system while conserving the mass of materials. When modelling multiple materials the use of independent advection algorithms for each material can lead to the problem of non-physical material overlap. A novel coupled flux limiter is developed to overcome this problem. This automatically generalises to arbitrary numbers of materials. Using the fully coupled (and rigorously verified) multi-material model, several geophysically relevant simulations are presented examining the generation of waves by landslides. The model is validated by demonstrating close agreement between model predictions and experimental results of wave generation, propagation and run-up. The simulations also showcase the powerful capabilities of an unstructured, adaptive multi-material model in real world scenarios.
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Yu, Hongnian. "Modelling and robust adaptive control of robot manipulators". Thesis, King's College London (University of London), 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.720361.
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Colman, Alan Wesley y n/a. "Role oriented adaptive design". Swinburne University of Technology, 2006. http://adt.lib.swin.edu.au./public/adt-VSWT20070320.110756.
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Software systems are becoming inexorably more open, distributed, pervasive, mobile and
connected. This thesis addresses the problem of how to build adaptive software systems.
These systems need to reliably achieve system-level goals in volatile environments, where
the system itself may be built from components of uncertain behaviour, and where the
requirements for the software system may be changing. This thesis adopts the systemtheoretic
concept of ontogenic adaptation from biology, and applies it to software
architecture. Ontogenic adaptation is the ability of an individual system to maintain its
organisational integrity by reconfiguring and regulating itself. A number of approaches to
adaptive software architecture have been recently proposed that, to varying degrees, enable
limited adaptive behaviour and reconfiguration, but none possess all the properties needed
for ontogenic adaptation. We introduce a meta-model and framework called Role Oriented
Adaptive Design (ROAD) that is consistent with the concept of maintaining organisational
integrity through ontogenic adaptation.
The ROAD meta-model defines software applications as networks of functional roles
which are executed by players (objects, components, services, agents, people, or rolecomposites).
These flexible organisational structures are adaptive because the relationships
(contracts) between roles, and the bindings between roles and players, can be regulated and
reconfigured at run-time. Such flexible organisational role-structures are encapsulated into
composites each with its own organiser. Because self-managed composites are themselves
role-players, these composites can be distributed and recursively composed. The organisers
of the composites form a management system over which requirements and performance
data pass. Rather than being monolithic constructions, ROAD software applications are
dynamic, self-managed compositions of loosely-coupled, and potentially, distributed
entities.
The concepts in the ROAD meta-model have been implemented in a programming
framework which can be extended by the application programmer to create adaptive
applications. Central to this framework are dynamic contracts. These contracts define the
role structure, control interactions between the role instances, and measure the performance
of those interactions. Adaptivity is achieved by monitoring and manipulating these
contracts, along with the role-player bindings. Contracts have been implemented using the
mechanism of �association aspects�.
The applicability of the ROAD framework to the domain of Service-Oriented
Computing is demonstrated. The framework is further evaluated in terms of its ability to
express the concept of ontogenic adaptation and also in terms of the overhead its runtime
infrastructure imposes on interactions.
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Neumann, Uwe. "An adaptive agent-based multicriteria simulation system". Thesis, Cranfield University, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.267214.
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Wahlbom, Hellström Victoria y Frida Alenius. "Investigation of Scale Adaptive Simulation (SAS) Turbulence Modelling for CFD-Applications". Thesis, Linköpings universitet, Mekanisk värmeteori och strömningslära, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-96363.
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Fluid dynamics simulations generally require large computational recourses in form of computer power and time. There are different methods for simulating fluid flows that are more or less demanding, but also more or less accurate. Two well known computational methods are the Reynolds Averaged Navier-Stokes (RANS) and Large Eddy Simulation (LES). RANS computes the timeaveraged flow properties, while LES resolve the large structures (eddies) of the flow directly and model the small ones. Hybrid models are combinations of these two models which have been developed to improve the RANS solutions and shorten the simulation time compared to LES computations. One such model is the Scale Adaptive Simulation (SAS) model which uses the RANS model in steady flow regions, such as close to walls, and a LES like model in unsteady regions with large fluctuations. This study was done for evaluating the SAS model compared to Unsteady RANS (URANS) and LES and their performance compared to measurements from an engineering point of view. This was done by running simulations on two different test cases, one external and one internal flow situation. The first one was flow around a wall-mounted cylinder and the second one was flow through an aorta with a coarctation in the descending aorta. The first test case was used to thoroughly evaluate the SAS model by running many simulations with URANS, SAS and LES with different element types, element sizes and flow parameters. The element types that have been analyzed are; tetrahedral, hexahedral and polyhedral. The results were compared with experiments done by Sumner et al. [7, 8, 9, 10]. The second test case was used for evaluating the SAS model even further on another flow situation. For this test case, only two SAS simulations were performed on two different grids; a structured hexahedral and an unstructured polyhedral. These results were compared with Magnetic Resonance Imaging (MRI) measurements obtained from Linköping University. No conclusion of which one of the simulated cases gives the best overall agreement with experimental results could be concluded from the obtained results. The best prediction of the drag coefficient for the cylinder was obtained for the coarsest polyhedral mesh that was run with LES, with the disagreement 0.4 percent. The best prediction of the Strouhal number was obtained for a URANS simulation performed on the coarsest mesh with an improved grid close to the cylinder surface, generating less than one, with a disagreement of 3 percent compared to measurements. For the meshes used, it was found that the polyhedral mesh gave the best overall results and the tetrahedral mesh gave the worst results for the cylinder case. For the aorta case the SAS model produced velocity components that had acceptable agreement with the MRI-measurements, but gave very poor results for the turbulent kinetic energy. The main conclusion of this thesis was that the SAS model performed better than URANS, but took longer time to compute simulations than LES, which was the model that generated the best overall results.
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Bell, Matthew J. "A framework for Adaptive Capability Profiling". Thesis, Loughborough University, 2015. https://dspace.lboro.ac.uk/2134/17476.
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This thesis documents research providing improvements in the field of accessibility modelling, which will be of particular interest as computing becomes increasingly ubiquitous. It is argued that a new approach is required that takes into account the dynamic relationship between users, their technology (both hardware and software) and any additional Assistive Technologies (ATs) that may be required. In addition, the approach must find a balance between fidelity and transportability. A theoretical framework has been developed that is able to represent both users and technology in symmetrical (hierarchical) recursive profiles, using a vocabulary that moves from device-specific to device-agnostic capabilities. The research has resulted in the development of a single unified solution that is able to functionally assess the accessibility of interactions through the use of pattern matching between graph-based profiles. A self-efficacy study was also conducted, which identified the inability of older people to provide the data necessary to drive a system based on the framework. Subsequently, the ethical considerations surrounding the use of automated data collection agents were discussed and a mechanism for representing contextual information was also included. Finally, real user data was collected and processed using a practically implemented prototype to provide an evaluation of the approach. The thesis represents a contribution through its ability to both: (1) accommodate the collection of data from a wide variety of sources, and (2) support accessibility assessments at varying levels of abstraction in order to identify if/where assistance may be necessary. The resulting approach has contributed to a work-package of the Sus-IT project, under the New Dynamics of Ageing (NDA) programme of research in the UK. It has also been presented to a W3C Research and Development Working Group symposium on User Modelling for Accessibility (UM4A). Finally, dissemination has been taken forward through its inclusion as an invited paper presented during a subsequent parallel session within the 8th International Conference on Universal Access in Human-Computer Interaction.
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Korale, Asoka Jeevaka Maligaspe. "Non-stationary adaptive signal prediction with error bounds". Thesis, Imperial College London, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.326258.
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Maloney, Alan. "Optimal (Adaptive) Design and Estimation Performance in Pharmacometric Modelling". Doctoral thesis, Uppsala universitet, Institutionen för farmaceutisk biovetenskap, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-182284.
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The pharmaceutical industry now recognises the importance of the newly defined discipline of pharmacometrics. Pharmacometrics uses mathematical models to describe and then predict the performance of new drugs in clinical development. To ensure these models are useful, the clinical studies need to be designed such that the data generated allows the model predictions to be sufficiently accurate and precise. The capability of the available software to reliably estimate the model parameters must also be well understood. This thesis investigated two important areas in pharmacometrics: optimal design and software estimation performance. The three optimal design papers progressed significant areas of optimal design research, especially relevant to phase II dose response designs. The use of exposure, rather than dose, was investigated within an optimal design framework. In addition to using both optimal design and clinical trial simulation, this work employed a wide range of metrics for assessing design performance, and was illustrative of how optimal designs for exposure response models may yield dose selections quite different to those based on standard dose response models. The investigation of the optimal designs for Poisson dose response models demonstrated a novel mathematical approach to the necessary matrix calculations for non-linear mixed effects models. Finally, the enormous potential of using optimal adaptive designs over fixed optimal designs was demonstrated. The results showed how the adaptive designs were robust to initial parameter misspecification, with the capability to "learn" the true dose response using the accruing subject data. The two estimation performance papers investigated the relative performance of a number of different algorithms and software programs for two complex pharmacometric models. In conclusion these papers, in combination, cover a wide spectrum of study designs for non-linear dose/exposure response models, covering: normal/non-normal data, fixed/mixed effect models, single/multiple design criteria metrics, optimal design/clinical trial simulation, and adaptive/fixed designs.
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Vea, Anne. "Modelling of Adaptive Geometry Flow Control Solutions in CFD". Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for energi- og prosessteknikk, 2012. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-19370.
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A synthetic jet is a flow control device which injects a pulsating jet flow of high-momentum fluid into a boundary layer near the wall confining a main flow. The technique is used to prevent or delay boundary layer separation. While the method is well reported for gas flows, less knowledge is available for liquid flows. It has been suggested that synthetic jets might be used in hydro turbines in order to stabilise draft tube flow. When accelerating a liquid flow, the energy consumption required will not only depend on the system mass, but also on the added mass due to acceleration of the liquid. The purpose of this thesis has been to study the physics of a synthetic jet where water is the working fluid, drawing special attention to added mass. CFD simulations have been conducted, where the synthetic jet was modelled using a dynamic grid. Results for added mass and frequency response of the system from CFD analysis have been compared to an analytic solution. CFD simulations seem to have captured a number of interesting effects not predicted from the analytic solution; the most prominent being frequency regions of lower added mass than analytically predicted. The apparent resonance regions are believed to occur due to interaction between the excitation frequency of the synthetic jet, and frequencies of dynamics in the system - examples are pressure pulsations from vortex shedding frequencies, or from frequencies originating from the effect of flow across a cavity. Furthermore, it has been demonstrated that operating the system at resonance will reduce the power requirements of the driving force, and that a variable stiffness spring should be part of the actuation system to allow for tuning of the resonance frequency.
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Welsh, Kristopher. "Design and run-time requirements modelling for adaptive systems". Thesis, Lancaster University, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.557291.
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This thesis explores the construction, enrichment and use of requirements models for adaptive systems. This thesis proposes the enrichment of adaptive systems' requirements models with additional tracing information, preserving the rationale behind configuration decisions. The preserved rationale can be utilised at design time, allowing decisions to be re-taken in the context of new or changed information and allowing for the identification of areas of uncertainty in understanding. The preserved rationale can also be used by a system itself, at run time, allowing it to adapt its behaviour to contexts not fully envisaged at design time. This thesis presents the ReAssuRE modelling process, which defines modelling perspectives from which some classes of adaptive system may be viewed. ReAssuRE models embed the described tracing information, and may be interpreted and reasoned with by a suitably constructed system at run time. This thesis presents tool support, allowing adaptive behaviour to be derived directly from ReAssuRE models. Finally, this thesis presents proof of concept components that allow a system to reason with ReAssuRE models, transforming them in response to monitored data, and derive new adaptive behaviour.
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El-Eraki, Sherif Mahmmoud Aly. "Modelling and combatting mobile FM multipath with adaptive equalizers". Thesis, University of Kent, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.410853.
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Donnelly, Peter Gerard. "Adaptive parametric modelling of narrowband signals for sonar applications". Thesis, University of Ulster, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.357582.
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Ai, Weilong. "Computational fracture modelling by an adaptive cracking particle method". Thesis, Durham University, 2018. http://etheses.dur.ac.uk/12679/.
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Conventional element-based methods for crack modelling suffer from remeshing and mesh distortion, while the cracking particle method is meshless and requires only nodal data to discretise the problem domain so these issues are addressed. This method uses a set of crack segments to model crack paths, and crack discontinuities are obtained using the visibility criterion. It has simple implementation and is suitable for complex crack problems, but suffers from spurious cracking results and requires a large number of particles to maintain good accuracy. In this thesis, a modified cracking particle method has been developed for modelling fracture problems in 2D and 3D. To improve crack description quality, the orientations of crack segments are modified to record angular changes of crack paths, e.g. in 2D, bilinear segments replacing straight segments in the original method and in 3D, nonplanar triangular facets instead of planar circular segments, so continuous crack paths are obtained. An adaptivity approach is introduced to optimise the particle distribution, which is refined to capture high stress gradients around the crack tip and is coarsened when the crack propagates away to improve the efficiency. Based on the modified method, a multi-cracked particle method is proposed for problems with branched cracks or multiple cracks, where crack discontinuities at crack intersections are modelled by multi-split particles rather than complex enrichment functions. Different crack propagation criteria are discussed and a configurational-force-driven cracking particle method has been developed, where the crack propagating angle is directly given by the configuration force, and no decomposition of displacement and stress fields for mixed-mode fracture is required. The modified method has been applied to thermo-elastic crack problems, where the adaptivity approach is employed to capture the temperature gradients around the crack tip without using enrichment functions. Several numerical examples are used to validate the proposed methodology.
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Pirrone, Angelo. "Decision modelling insights in cognition and adaptive decision making". Thesis, University of Sheffield, 2016. http://etheses.whiterose.ac.uk/15841/.
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Fernandez, Telleria Bernardo Xavier. "Essays on real business cycle modelling under adaptive learning". Thesis, University of Glasgow, 2013. http://theses.gla.ac.uk/4216/.
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The thesis consists on three chapters aiming to contribute to a growing literature on adaptive learning, a form of bounded rationality that has been attracting increasing interest both in the theoretical and practical fields, as an alternative to the commonly used rational expectations hypothesis on how expectations are formed among economic agents. The first chapter investigates whether it is possible to improve the ability of the standard real business cycle model to match the main stylised facts of emerging economies, taking the case of Mexico as an illustration, by assuming that agents are not fully rational and instead form expectations according to an adaptive learning rule. Two well-known rules - recursive least squares and its constant gain variant - are considered for this purpose. The degree of difficulty of the learning process is characterised by different starting values of the algorithms as well as different constant gains. The simulations show that the model under learning generally outperforms its rational expectations counterpart. Therefore, policymakers should take into account the fact that the expected welfare gains/losses of a particular policy reform, conceived assuming a fully-rational environment, might be significantly different if, in practice, agents behave as learners. Using a heterogeneous-agent model with three types of agents, namely capitalists, skilled workers and unskilled workers - assuming constant population shares suggesting low social mobility -, and allowing for different degrees of complementarity among these within the productive structure, the second chapter welfare-evaluates tax reforms consistent with a lower long run debt-to-output ratio for the United Kingdom, both under rational expectations and heterogenous learning. This chapter shows that, relative to the other tax reforms, capital tax cuts lead to the highest aggregate welfare but are skill-biased and can thus increase inequality in the long run. That is, depending on the elasticity of substitution between capital and unskilled labour, falls in the capital tax can result in higher levels of welfare inequality, even in the absence of other frictions and increases in other forms of taxation. On the other hand, reductions in labour taxes can hurt the capitalists. This chapter shows too that including the transition period in the welfare evaluation lowers the inequality effects of capital tax reductions since the complementarity between capital and all labour inputs is higher in the short- than in the long-run. Finally, while heterogeneous learning in the shape of differing initial beliefs after the reform can lead to a form of "irrational exuberance" after a tax cut, it can also exacerbate welfare inequality. Finally, the third chapter presents an heterogeneous-agent model with two types of agents, capitalists and workers - with constant population shares given the strong evidence on low social mobility -, calibrated to Bolivia´s data in order to examine the short and long-run effectiveness and distributional effects of various fiscal rules designed to impose restrictions on the evolution of public debt as a share of output, in response to two different sources of exogenous volatility (i.e. productivity and commodity shocks) and under different ways of forming expectations, namely rational expectations and heterogenous learning. The results show that under full rationality the fiscal rules generate a trade-off between debt-stabilisation and higher income inequality while, under some conditions, heterogenous learning can help to break such trade-off so that some of the rules can perform well in both fields. However, given the significantly high levels of income inequality and dependence on commodity revenues experienced by Bolivia, finding the best performing rule in response to all the relevant exogenous shocks this economy might face, appears to be a challenging task.
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Cheung, Ronnie Chu-ting. "An adaptive modelling infrastructure for context-aware mobile computing". Thesis, London Metropolitan University, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.549553.
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Context provides information about the present status of people, places, things, network and devices in the environment. Context-awareness refers to the use of context information for an application to adapt its functionality to the current context of use. Development of context-aware applications is inherently complex. Previous researches on mobile computing emphasize on programmable interfaces for development of context-aware systems. There are limited researches that emphasize on the modelling aspects of adaptive applications. This research aims at developing a complete infrastructure for development of context-aware applications. The infrastructure consists of a middleware for context-aware application development that is supported by a set of context information modelling and reasoning facilities. It aims at extending the capabilities of context-aware middleware infrastructures by incorporating novel approaches to model context and situations under uncertainty. This thesis addresses the key challenges in context-aware computing by a complete infrastructure that aims at achieving the following: (1) support for fuzzy composition of high level context abstraction from low level detector context, and fuzzy-based inference mechanisms, (2) support for mobile services that can be dynamically composed and migrated with reference to adaptation requirements for different context situations, (3) support for modelling of adaptation components and entities.
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Abdelhamid, S. "Respiratory motion modelling and predictive tracking for adaptive radiotherapy". Thesis, Coventry University, 2010. http://curve.coventry.ac.uk/open/items/f135cb12-e9f9-1e4f-9c57-6de2fc378069/1.
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External beam radiation therapy (EBRT) is the most common form of radiation therapy (RT) that uses controlled energy sources to eradicate a predefined tumour volume, known as the planning target volume (PTV), whilst at the same time attempting to minimise the dose delivered to the surrounding healthy tissues. Tumours in the thoracic and abdomen regions are susceptible to motion caused mainly by the patient respiration and movement that may occur during the treatment preparation and delivery. Usually, an adaptive approach termed adaptive radiation therapy (ART), which involves feedback from imaging devices to detect organ/surrogate motion, is considered. The feasibility of such techniques is subject to two main problems. First, the exact position of the tumour has to be estimated/detected in real-time and second, the delay that can arise from the tumour position acquisition and the motion tracking compensation. The research work described in this thesis is part of the European project entitled ‘Methods and advanced equipment for simulation and treatment in radiation oncology’ (MAESTRO), see Appendix A. The thesis presents both theoretical and experimental work to model and predict the respiratory surrogate motion. Based on a widely investigated clinical internal and external respiratory surrogate motion data, two new approaches to model respiratory surrogate motion were developed. The first considers the lung as a bilinear model that replicates the motion in response to a virtual input signal that can be seen as a signal generated by the nervous system. This model and a statistical model of the respiratory period and duty cycle were used to generate a set of realistic respiratory data of varying difficulties. The aim of the latter was to overcome the lack of test data for a researcher to evaluate their algorithms. The second approach was based on an online polynomial function that was found to adequately replicate the breathing cycles of regular and irregular data, using the same number of parameters as a benchmark sinusoidal model.
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Georgiou, Theodosis. "User modelling for adaptive training in high performance driving". Thesis, Imperial College London, 2016. http://hdl.handle.net/10044/1/43533.
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User model creation is a fundamental component for the development of intelligent personalised systems. This thesis proposes an adaptive user modelling framework that uses a combination of unobtrusive task-related and physiological data with the aim of identifying strengths and weaknesses in user performance in the defined task. The research is focused on utilising the framework to provide personalised content adaptation in car racing games. Our system adopts concepts from the Trace Theory (TT) framework, and uses machine learning techniques to extract specific features from the user and the game. These metrics are then transformed and evaluated into higher level abstractions such as experience, exploration and physiological attention by utilising the educational theoretical frameworks of Flow and Zone Theory. The end result is to provide new game paths utilising the user’s model. We demonstrate that this procedural generation of user-tailored content drives the self-motivating behaviour of players to immerse and engage themselves in the game’s virtual world. Collection of data and feedback from multiple users (52) allowed us to associate the model’s outcomes to the user responses, as well as device multiple trial scenarios to verify their training and engagement. We have also evaluated the algorithms for the generation of new tracks for their suitability on the skill’s profile of 41 of our subjects and race track diversity among the evolved paths. We have also designed a method for predicting the states of the user-controlled system by combining information from both sources – vehicle and user – via Gaussian Processes (GPs). In the context of high speed car racing we showed that the forthcoming position and speed of the car can be predicted with high accuracy by our trained user models. This opens up future possibilities of generating better personalised tracks for individuals or even real-time share-control of the car to optimally assist the users in dangerous situations.
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Abdullah, Sophiana Chua. "Student modelling by adaptive testing : a knowledge-based approach". Thesis, University of Kent, 2003. https://kar.kent.ac.uk/13956/.
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An adaptive test is one in which the number of test items and the order in which the items are presented are computed during the delivery of the test so as to obtain an accurate estimate of a student's knowledge, with a minimum number of test items. This thesis is concerned with the design and development of computerised adaptive tests for use within educational settings. Just as, in the same setting, intelligent tutoring systems are designed to emulate human tutors, adaptive testing systems can be designed to mimic effective informal examiners. The thesis focuses on the role of adaptive testing in student modelling, and demonstrates the practicality of constructing such tests using expert emulation. The thesis makes the case that, for small scale adaptive tests, a construction process based on the knowledge acquisition technique of expert systems is practical and economical. Several experiments in knowledge acquisition for the construction of an adaptive test are described, in particular, experiments to elicit information for the domain knowledge, the student model and the problem progression strategy. It shows how a description of a particular problem domain may be captured using traditional techniques that are supported by software development in the constraint logic extension to Prolog. It also discusses knowledge acquisition techniques for determining the sequence in which questions should be asked. A student modelling architecture called SKATE is presented. This incorporates an adaptive testing strategy called XP, which was elicted from a human expert. The strategy, XP, is evaluated using simulations of students. This approach to evaluation facilitates comparisons between approaches to testing and is potentially useful in tuning adaptive tests.
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Francisco-Revilla, Luis. "Multi-model adaptive spatial hypertext". Texas A&M University, 2004. http://hdl.handle.net/1969.1/1444.
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Information delivery on the Web often relies on general purpose Web pages that require the reader to adapt to them. This limitation is addressed by approaches such as spatial hypermedia and adaptive hypermedia. Spatial hypermedia augments the representation power of hypermedia and adaptive hypermedia explores the automatic modification of the presentation according to user needs. This dissertation merges these two approaches, combining the augmented expressiveness of spatial hypermedia with the flexibility of adaptive hypermedia.
This dissertation presents the Multi-model Adaptive Spatial Hypermedia framework (MASH). This framework provides the theoretical grounding for the augmentation of spatial hypermedia with dynamic and adaptive functionality and, based on their functionality, classifies systems as generative, interactive, dynamic or adaptive spatial hypermedia.
Regarding adaptive hypermedia, MASH proposes the use of multiple independent models that guide the adaptation of the presentation in response to multiple relevant factors. The framework is composed of four parts: a general system architecture, a definition of the fundamental concepts in spatial hypermedia, an ontological classification of the adaptation strategies, and the philosophy of conflict management that addresses the issue of multiple independent models providing contradicting adaptation suggestions.
From a practical perspective, this dissertation produced WARP, the first MASH-based system. WARPs novel features include spatial transclusion links as an alternative to navigational linking, behaviors supporting dynamic spatial hypermedia, and personal annotations to spatial hypermedia. WARP validates the feasibility of the multi-model adaptive spatial hypermedia and allows the exploration of other approaches such as Web-based spatial hypermedia, distributed spatial hypermedia, and interoperability issues between spatial hypermedia systems.
In order to validate the approach, a user study comparing non-adaptive to adaptive spatial hypertext was conducted. The study included novice and advanced users and produced qualitative and quantitative results. Qualitative results revealed the emergence of reading behaviors intrinsic to spatial hypermedia. Users moved and modified the objects in order to compare and group objects and to keep track of what had been read. Quantitative results confirmed the benefits of adaptation and indicated a possible synergy between adaptation and expertise. In addition, the study created the largest spatial hypertext to date in terms of textual content.
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Yuan, Qiang. "Adaptive, statistical, context modelling for predictive coding of medical images". Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp04/mq21056.pdf.
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Narayanan, Vidya. "A learning based approach to modelling bilateral adaptive agent negotiations". Thesis, University of Southampton, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.485525.
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In large multi-agent systems, individual agents often have conflicting goals, but are dependent on each other for the achievement of these objectives. In such 'situations, negotiation between the agents is a key means of resolving conflicts and reaching a compromise. Hence it is imperative to develop good automated negotiation techniques to enable effective interactions. However this problem is made harder by the fact that such environments are invariably dynamic (e.g. the bandwidth available for COmInUnications can fluctuate, the. availability of computation resources can change, and the time available for negotiations can change). Moreover, these changes can have a direct eff~ct on the negotiation process. Thus an agent has to adapt its negotiation behaviour in response to changes in the environment and its opponent's behaviour if it is to be effective. Given this, this research has developed negotiation mechanisms that enable an agent to perform effectively in a particular class of negotiation encounters; namely, .~ bilateral negotiation in which a service provider and a service consumer interact to fix the price of the service. In more detail, we use both reinforcement and Bayesian learning methods to derive an optimal agent strategy for bilateral negotiations in dynamic environments with incomplete information. Specifically, an agent models the change in its opponent's behaviour using Markov Chains and determines an optimal policy to use in response to changes in the environment. Also using the Markov chain framework, the agent updates its prior knowledge of the opponent by observing successive offers using Bayesian inference and hence strategically responds to its opponent. This framework for adaptive negotiation in non-stationary environments incorporates two novel learning algorithms that use reinforcement and Bayesian learning techniques to respond to the various forms of dynamism. Having devised the algorithms, we analytically show that the former learns an optimal policy for negotiating in a non-stationary environment and the latter converges over repeated encounters to the opponent's true strategic model. These empirical results show that the reinforcement learning.algorithm successfully concludes 83% of the negotiations in dynamic scenarios and that when using the Bayesian algorith?l the opponent learns the true model of an adaptive opponent's behaviour in 95% of the encounters. Both of these results compare very favourably with the previous state of art. We have also done a comparison of the these two algorithms. The empirical results show that using reinforcement learning a very high percentage (90%) of dynamic. ne- .' gotiation encounters end in agreement, whereas using Bayesian learning techniques the agent eams a large share ofthe profits (89%) in the negotiation process.
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Pavlidis, Dimitrios. "Modelling urban air quality using mesh adaptive large-eddy simulation". Thesis, Imperial College London, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.538680.
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Liu, Wenguo. "Design and Modelling of Adaptive Foraging in Swarm Robotic Systems". Thesis, University of the West of England, Bristol, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.495460.
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Swann robotics is a new approach to coordinate the behaviours of large number of relatively simple robots in decentralised manner. As the robots in the swann have only local perception and very limited local communication abilities, one of the challenges in designing swann robotic systems with desired collective behaviour is to understand the effect of individual behaviour on the group performance. This thesis dedicates the research on design and optimisation of interaction rules for a group of foraging robots that try to achieve energy efficiency collectively. The investigation starts with designing a set of interaction rules for the individual robots, inspired from the widely observed self-organisation phenomenon in biological system, so as improve the energy efficiency at the group level. A threshold-based controller, using two internal time thresholds - resting time and searching time threshold, is introduced to regulate the behaviours for the robot in order to improve the energy efficiency. Three cues: internal cues, social cues and environmental cues are then proposed to adjust the internal time thresholds in a self-organised manner. A number of strategies have been developed by combining these three cues and applied to the collective foraging task. Although the simulation results show that the robot swarm with adaptation mechanisms has the ability to guide the system towards energy optimisation collectively, there are difficulties in manually finding a set of parameters for the adaptation algorithm which can lead to the best energy efficiency under certain environmental conditions. This thesis focuses most of its effort into developing a macroscopic probabilistic model to understand the effect of individual parameters (internal time thresholds) on the performance of the system and therefore help to design the adaptation algorithm more efficiently. The modelling work is divided in two stages: A simplified situation for a swarm of homogeneous foraging robots without adaptation mechanism is considered first, then the macroscopic probabilistic model is extended for a robot swann with full adaptation ability. 3 The essential idea of the probabilistic modelling approach is to treat the interactions among robots, or between robots and environment, as stochastic events. First, a probabilistic finite state machine (PFSM), adapted from the robot controller, is used to describe the foraging task at the group level. A number of difference equations are then developed to capture the change of number of robot in each state. The state transition probabilities and other parameters used in the model are obtained through a novel geometrical approach, which makes sure that no free parameters exist in the model. In addition, the adaptation rules are encoded into the difference equations by introducing the concept of private resting/searching time thresholds and public resting/searching time thresholds. The proposed macroscopic model has been validated using simulation. The results show that the model achieves very good accuracy in predicting the net energy of the swarm, not only in the final stage but also in the instantaneous level. Finally, with the extended macroscopic model, a real-coded steady-state genetic algorithm (GA) is introduced to simplify the process of parameters selection for the adaptation algorithms. Experiments are carried out using the the best set of parameters found by the GA. It shows that the robot swarm with selected parameters can achieve a near-optimal energy efficiency under different environmental conditions.
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Thomas, Stephen Malcolm. "Adaptive nonlinear modelling of the W30 helicopter using neural networks". Thesis, University of Warwick, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.319813.
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