Dissertations / Theses on the topic 'Complex adaptive systems'
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Bondorowicz, Stefan. "Adaptive control of complex dynamic systems." Thesis, University of Oxford, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.302787.
Full textKingston, Kenneth Samuel. "Applications of complex adaptive systems approaches to coastal systems." Thesis, University of Plymouth, 2003. http://hdl.handle.net/10026.1/474.
Full textShenoy, Rajiv. "Overset adaptive strategies for complex rotating systems." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/51796.
Full textMorris, 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.
Full textHammer, Roger Julius. "Strategy development process and complex adaptive systems." Thesis, Aston University, 2011. http://publications.aston.ac.uk/15812/.
Full textKennedy, Cameron. "Mass media and media complex adaptive systems, towards a complex methodology." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape9/PQDD_0002/MQ43352.pdf.
Full textKennedy, Cameron (Cameron John) Carleton University Dissertation Journalism and Communication. "Mass media and media complex adaptive systems; towards a complex methodology." Ottawa, 1999.
Find full textEngler, Joseph John. "Innovation as a complex adaptive system." Thesis, University of Iowa, 2009. https://ir.uiowa.edu/etd/233.
Full textJefferies, Paul. "Emergent phenomena of complex adaptive systems : financial markets." Thesis, University of Oxford, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.427625.
Full textFonseca, Jose Manuel Lopes Da. "Innovation : a property of complex adaptive social systems." Thesis, University of Hertfordshire, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.263031.
Full textAtkinson, Simon Reay. "Engineering design adaptation fitness in complex adaptive systems." Thesis, University of Cambridge, 2014. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.648674.
Full textDougherty, Francis Laverne. "A Complex Adaptive Systems Analysis of Productive Efficiency." Diss., Virginia Tech, 2014. http://hdl.handle.net/10919/65146.
Full textPh. D.
Sommerer, Christa. "Modeling complex adaptive systems and complexity for interactive art." Thesis, University of South Wales, 2002. https://pure.southwales.ac.uk/en/studentthesis/modeling-complex-adaptive-systems-and-complexity-for-interactive-art(3d7143e3-eb05-49b9-8965-0ffa53767eb9).html.
Full textBrosi, Dennis. "Examining Emergent Strategy Approaches With Complex Adaptive Systems Principles." St. Gallen, 2009. http://www.biblio.unisg.ch/org/biblio/edoc.nsf/wwwDisplayIdentifier/03604899101/$FILE/03604899101.pdf.
Full textChoe, Sehyo Charley. "Models of complex adaptive systems with underlying network structure." Thesis, University of Oxford, 2007. https://ora.ox.ac.uk/objects/uuid:1cb8cb96-d27f-4543-9065-0e38a4297435.
Full textLaine, Tei. "Agent-based model selection framework for complex adaptive systems." [Bloomington, Ind.] : Indiana University, 2006. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3229580.
Full text"Title from dissertation home page (viewed July 10, 2007)." Source: Dissertation Abstracts International, Volume: 67-08, Section: B, page: 4523. Adviser: Filippo Menczer.
Chow, Fung-kiu, and 鄒鳳嬌. "Modeling the minority-seeking behavior in complex adaptive systems." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2003. http://hub.hku.hk/bib/B29367487.
Full textSullivan, John P. "Emergent Learning: Three Learning Communities as Complex Adaptive Systems." Thesis, Boston College, 2009. http://hdl.handle.net/2345/663.
Full textIn the 2007-2008 school year, the author conducted a collaborative case study (Stake, 2000) with the goal of discovering and describing "emergent learning" in three high school classrooms. Emergent learning, defined as the acquisition of new knowledge by an entire group when no individual member of the group possessed it before, is implied by the work of many theorists working on an educational analog of a natural phenomenon called a complex adaptive system. Complex adaptive systems are well networked collectives of agents that are non-linear, bounded and synergistic. The author theorized that classes that maximized the features of complex adaptive systems could produce emergent learning (a form of synergy), and that there was a continuum of this complexity, producing a related continuum of emergence. After observing a co-curricular jazz group, an English class, and a geometry class for most of one academic year, collecting artifacts and interviewing three students and a teacher from each class, the author determined that there was indeed a continuum of complexity. He found that the actively complex nature of the Jazz Rock Ensemble produced an environment where emergence was the norm, with the ensemble producing works of music, new to the world, with each performance. The English section harnessed the chaotic tendencies of students to optimize cognitive dissonance and frequently produce emergent learning, while the mathematics section approached the learning process in a way that was too rigidly linear to allow detectable emergence to occur
Thesis (PhD) — Boston College, 2009
Submitted to: Boston College. Lynch School of Education
Discipline: Teacher Education, Special Education, Curriculum and Instruction
Ram, Kadambari. "A Complex Systems Simulation Study for Increasing Adaptive-Capacity." ScholarWorks, 2017. https://scholarworks.waldenu.edu/dissertations/4477.
Full textGeorge, David Frederick James. "Reconfigurable cellular automata computing for complex systems on the SPACE machine /." Connect to this title, 2005. http://theses.library.uwa.edu.au/adt-WU2006.0020.
Full textPrasad, Kumkum. "Organisations as complex adaptive systems : implications for the design of information systems." Thesis, Open University, 1998. http://oro.open.ac.uk/57909/.
Full textMcQuesten, Pamela Ann. "Human action in mass communication : a complex adaptive systems approach /." Digital version accessible at:, 1998. http://wwwlib.umi.com/cr/utexas/main.
Full textYoder-Bontrager, Daryl. "Nongovernmental organizations in disaster and coordination| A complex adaptive systems view." Thesis, University of Delaware, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=1585187.
Full textNongovernmental organizations (NGOs) play a major role in disasters around the world. As they carry out disaster work NGOs are often grouped together as the "NGO sector," although their varied size, scope, focus and country of origin make generalizations difficult. Coordinating NGO disaster work has been an ongoing challenge for governments and for NGOs themselves for reasons ranging from the wishes of NGO funders to uncertainty about what coordination means to competition for funds.
This thesis uses a complex adaptive system (CAS) framework to understand how NGOs may coordinate their own work. A complex adaptive system is made up of a set of independent agents that interact with each other to form a whole entity without the benefit of an explicit central control mechanism.
The qualitative study carried out semi-structured interviews with 16 NGOs active in disaster in Honduras to explore to what extent their interactions conformed to six characteristics of complex adaptive systems - 1) schemata; 2) self-organization; 3) communication and information; 4) rules; 5) learning and adaptation; and 6) aggregate outcomes, and relations with government.
Results of the interviews showed that many NGOs have multiple links among themselves with active communication channels that depend heavily on personal relationships. Interviews showed that collaboration among NGOs has increased over the past decade, although the degree of cooperation among them was inconsistent. Interviewees found it difficult to name an aggregate system-wide outcome. Government relations were found to be mixed - many NGOs had both positive and negative things to say about their relationships with government.
The NGOs were found to have both characteristics of a CAS and factors that did not fit a CAS description. NGOs must continually invest energy to maintain a system because entropic forces away from increased organization remain strong.
Ho, Ki-hiu, and 何其曉. "Extracting real market behavior in complex adaptive systems through minority game." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B30163705.
Full textDickens, Peter Martin. "Facilitating Emergence: Complex, Adaptive Systems Theory and the Shape of Change." Antioch University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=antioch1339016565.
Full textChaoui, Hicham. "Soft-computing based intelligent adaptive control design of complex dynamic systems." Thèse, Université du Québec à Trois-Rivières, 2011. http://depot-e.uqtr.ca/2676/1/030295752.pdf.
Full textOnik, Mohammad Fakhrul Alam. "Business value of information technology: A complex adaptive systems theory view." Thesis, Queensland University of Technology, 2019. https://eprints.qut.edu.au/132323/1/Mohammad%20Fakhrul%20Alam_Onik_Thesis.pdf.
Full textGeorge, David Frederick James. "Reconfigurable cellular automata computing for complex systems on the SPACE machine." University of Western Australia. School of Computer Science and Software Engineering, 2006. http://theses.library.uwa.edu.au/adt-WU2006.0020.
Full textMajor, Sarah J. "Building Resilience: A Complex Systems Approach to Sustainable Design." University of Cincinnati / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1337363724.
Full textFath, Janet Louise. "An architecture for adaptive computer-assisted instruction programs for complex dynamic systems." Diss., Georgia Institute of Technology, 1987. http://hdl.handle.net/1853/33442.
Full textLiu, Ying. "Complex-valued adaptive digital signal enhancement for applications in wireless communication systems." Doctoral diss., University of Central Florida, 2012. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5405.
Full textPh.D.
Doctorate
Electrical Engineering and Computer Science
Engineering and Computer Science
Electrical Engineering
Guo, Donghang. "Large-Scale Simulations for Complex Adaptive Systems with Application to Biological Domains." Diss., Virginia Tech, 2007. http://hdl.handle.net/10919/26403.
Full textPh. D.
Lentenbrink, Laura. "The Impact of Adaptive Leadership Capacity on Complex Organizational Health Systems Outcomes." ScholarWorks, 2017. https://scholarworks.waldenu.edu/dissertations/3619.
Full textNel, Darren Henry. "Exploring a complex adaptive systems approach to the study of urban change." Diss., University of Pretoria, 2015. http://hdl.handle.net/2263/56093.
Full textDissertation (MTRP)--University of Pretoria, 2015.
tm2016
Town and Regional Planning
MTRP
Unrestricted
Held, Fabian Philipp. "Modelling the Evolution of Business Relationships and Networks as Complex Adaptive Systems." Thesis, The University of Sydney, 2013. http://hdl.handle.net/2123/8999.
Full textYeo, Narelle Fiona. "“THE INFALLIBLE PROTAGONIST” A STUDY OF COMPLEXITY THEORY AND REHEARSAL DYNAMICS IN MONODRAMA." Thesis, The University of Sydney, 2017. http://hdl.handle.net/2123/16418.
Full textViveca, Lindahl. "Optimizing sampling of important events in complex biomolecular systems." Doctoral thesis, KTH, Fysik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-217837.
Full textQC 20171117
Espinosa, Jennifer Anne. "Understanding the Complexity of Product Returns Management: A Complex Adaptive Systems Theory Perspective." Scholar Commons, 2016. http://scholarcommons.usf.edu/etd/6233.
Full textLeduc, Nathaniel. "Understanding Collaboration in the Context of Loosely- and Tightly-Coupled Complex Adaptive Systems." Thesis, Université d'Ottawa / University of Ottawa, 2018. http://hdl.handle.net/10393/37087.
Full textMohamad, Mustafa A. "Direct and adaptive quantification schemes for extreme event statistics in complex dynamical systems." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/113542.
Full textCataloged from PDF version of thesis.
Includes bibliographical references (pages 171-183).
Quantifying extreme events is a central issue for many technological processes and natural phenomena. As extreme events, we consider transient responses that push the system away from its statistical steady state and that correspond to large excursions. Complex systems exhibiting extreme events include dynamical systems found in nature, such as the occurrence of anomalous weather and climate events, turbulence, formation of freak waves in the ocean and optics, and dynamical systems in engineering applications, including mechanical components under environmental loads, ship rolling and capsizing, critical events in power grids, as well as chemical reactions and conformational changes in molecules. It has been recognized that extreme events occur more frequently than Gaussian statistics suggest and thus occur often enough that they have practical consequences, and sometimes catastrophic outcomes, that are important to understand and predict. A hallmark characteristic of extreme events in complex dynamical systems is non-Gaussian statistics (e.g. heavy-tails) in the probability density function (pdf) describing the response of their observables. For engineers and applied mathematicians, a central issue is how to efficiently and accurately describe this non-Gaussian behavior. For random dynamical systems with inherently nonlinear dynamics, expressed through intermittent events, nonlinear energy transfers, broad energy spectra, and large intrinsic dimensionality, it is largely the case that we are limited to (direct) Monte-Carlo sampling, which is too expensive to apply in real-world applications. To address these challenges, we present both direct and adaptive (sampling based) strategies designed to quantify the probabilistic aspects of extreme events in complex dynamical systems, effectively and efficiently. Specifically, we first develop a direct quantification framework that involves a probabilistic decomposition that separately considers intermittent, extreme events from the background stochastic attractor of the dynamical system. This decomposition requires knowledge of the dynamical mechanisms that are responsible for extreme events and partitions the phase space accordingly. We then apply different uncertainty quantification schemes to the two decomposed dynamical regimes: the background attractor and the intermittent, extreme-event component. The background component, describing the 'core' of the pdf, although potentially very high-dimensional, can be efficiently described by uncertainty quantification schemes that resolve low-order statistics. On the other hand, the intermittent component, related to the tails, can be described in terms of a low-dimensional representation by a small number of modes through a reduced order model of the extreme events. The probabilistic information from these two regimes is then synthesized according to a total probability law argument, to effectively approximate the heavy-tailed, non-Gaussian probability distribution function for quantities of interest. The method is demonstrated through numerous applications and examples, including the analytical and semi-analytical quantification of the heavy-tailed statistics in mechanical systems under random impulsive excitations (modeling slamming events in high speed craft motion), oscillators undergoing transient parametric resonances and instabilities (modeling ship rolling in irregular seas and beam bending), and extreme events in nonlinear Schrodinger based equations (modeling rogue waves in the deep ocean). The proposed algorithm is shown to accurately describe tail statistics in all of these examples and is demonstrated to be many orders of magnitude faster than direct Monte-Carlo simulations. The second part of this thesis involves the development of adaptive, sampling based strategies that aim to accurately estimate the probability distribution and extreme response statistics of a scalar observable, or quantity of interest, through a minimum number of experiments (numerical simulations). These schemes do not require specialized knowledge of the dynamics, nor understanding of the mechanism that cause or trigger extreme responses. For numerous complex systems it may not be possible or very challenging to analyze and quantify conditions that lead to extreme responses or even to obtain an accurate description of the dynamics of all the processes that are significant. To address this important class of problems, we develop a sequential algorithm that provides the next-best design point (set of experimental parameters) that leads to the largest reduction in the error of the probability density function estimate for the scalar quantity of interest when the adaptively predicted design point is evaluated. The proposed algorithm utilizes Gaussian process regression to infer dynamical properties of the quantity of interest, which is then used to estimate the desired pdf along with uncertainty bounds. We iteratively determine new design points through an optimization procedure that finds the optimal point in parameter space that maximally reduces uncertainty between the estimated bounds of the posterior pdf estimate of the observable. We provide theorems that guarantee convergence of the algorithm and analyze its asymptotic behavior. The adaptive sampling method is illustrated to an example in ocean engineering. We apply the algorithm to estimate the non-Gaussian statistics describing the loads on an offshore platform in irregular seas. The response of the platform is quantified through three-dimensional smoothed particle hydrodynamics simulations. Because of the extreme computational cost of these numerical models, quantification of the extreme event statistics for such systems has been a formidable challenge. We demonstrate that the adaptive algorithm accurately quantifies the extreme event statistics of the loads on the structure through a small number of numerical experiments, showcasing that the proposed algorithm can realistically account for extreme events in the design and optimization processes for large-scale engineering systems.
by Mustafa A. Mohamad.
Ph. D.
Murray, D. "Real-time stimulation for exercising complex systems employing adaptive sensors and sensor arrays." Thesis, University College London (University of London), 2013. http://discovery.ucl.ac.uk/1397142/.
Full textWhiteley, Jervis. "Complex Adaptive Systems and Conversation Analysis: A New Perspective for Consumer Behaviour Research?" Thesis, Curtin University, 2002. http://hdl.handle.net/20.500.11937/734.
Full textWhiteley, Jervis. "Complex Adaptive Systems and Conversation Analysis: A New Perspective for Consumer Behaviour Research?" Curtin University of Technology, Graduate School of Business, 2002. http://espace.library.curtin.edu.au:80/R/?func=dbin-jump-full&object_id=12936.
Full textData were transcribed and analysed for all sessions according to the conventions of conversation analysis. In the meeting-room sessions, data were also collected by electronic-group-support-systems technology and subjected to a modified form of content analysis. The broad findings showed the following. The assumption that there was little evidence of interest in complex adaptive systems among consumer behaviour researchers was confirmed. Apart from one paper calling for the use of conversation analysis in consumer behaviour research, there appeared to have been no subsequent reports of its adoption. The potential for conversation analysis in consumer research has probably not been understood because it was seen as a data-collection method only within an ethnomethodological perspective. The discursive theoretical perspective, which gives a prime position to conversation analysis in the construction of factual accounts, was found to be an innovative way to study consumer behaviour. A discursive theoretical research perspective could have provided a more robust theoretical justification for the fieldwork carried out in this study than the theory of the methodology that was first developed for this study. Conversation analysis did meet the five criteria proposed for surfacing a complex adaptive system in a small group but in an unexpected way. It met these criteria through the research process. In other words, by setting up an appropriate research environment and using conversation analysis, it was shown that a complex adaptive system was in operation.
An outcome of employing complex adaptive systems theory and conversation analysis is a new way of seeing groups of consumers as a self-organised, nonlinear, interactive entity. Conversation analysis has proven to be a method of empirically observing this entity, whilst preserving the consumer groups' complex adaptiveness. There were three conclusions. The first is that the discursive paradigm appears to be an alternative paradigm for consumer behaviour research that is appropriate for certain applications. For example, marketing communications and word-of-mouth communication. The second conclusion is that when small-group talk-in-interaction is recorded and analysed using conversation analysis, the characteristics of a complex adaptive system theorised in this study seem evident to the researcher. The third is that complex adaptive systems appear to be capable of being researched in the field, but more work is needed on defining the characteristics to be researched.
Oliver, John M. "Multi-objective optimisation methods applied to complex engineering systems." Thesis, Cranfield University, 2014. http://dspace.lib.cranfield.ac.uk/handle/1826/11707.
Full textRussell, Carol Faculty of Engineering UNSW. "E-learning adoption in a campus university as a complex adaptive system: mapping lecturer strategies." Awarded by:University of Leicester, 2008. http://handle.unsw.edu.au/1959.4/39597.
Full textau, Helenallison@ozemail com, and Helen Elizabeth Allison. "Linked Social-Ecological Systems: A Case Study of The Resilience of The Western Australian Agricultural Region." Murdoch University, 2003. http://wwwlib.murdoch.edu.au/adt/browse/view/adt-MU20040730.144640.
Full textRanganathan, Raghuram. "Novel complex adaptive signal processing techniques employing optimally derived time-varying convergence factors with applications in digital signal processing and wireless communications." Orlando, Fla. : University of Central Florida, 2008. http://purl.fcla.edu/fcla/etd/CFE0002431.
Full textDeshpande, Aditya. "Robot Swarm Based On Ant Foraging Hypothesis With Adaptive Levy Flights." University of Cincinnati / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1504780906566663.
Full textLeMaster, Cheryl Faye. "Leading Change in Complex Systems: A Paradigm Shift." Antioch University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=antioch1500033972019138.
Full textHentati-Sundberg, Jonas. "SEA CHANGE : Social-ecological co-evolution in Baltic Sea fisheries." Doctoral thesis, Stockholms universitet, Stockholm Resilience Centre, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-122372.
Full textAt the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 5: Manuscript.