Дисертації з теми "Neural network inversion"
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Jakobsson, Henrik. "Inversion of an Artificial Neural Network Mapping by Evolutionary Algorithms with Sharing." Thesis, University of Skövde, Department of Computer Science, 1998. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-165.
Повний текст джерелаInversion of the artificial neural network mapping is a relatively unexplored field of science. By inversion we mean that a search is conducted to find what input patterns that corresponds to a specific output pattern according to the analysed network. In this report, an evolutionary algorithm is proposed to conduct the search for input patterns. The hypothesis is that the inversion with the evolutionary search-method will result in multiple, separate and equivalent input patterns and not get stuck in local optima which possibly would cause the inversion to result in erroneous answer. Beside proving the hypothesis, the tests are also aimed at explaining the nature of inversion and how the result of inversion should be interpreted. At the end of the document a long list of proposed future work is suggested. Work, which might result in a deeper understanding of what the inversion means and maybe an automated analysis tool, based on inversion.
Sopoco, Tara Helene. "A neural network technique for atmospheric inversion of WINDII and OSIRIS data." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/MQ57998.pdf.
Повний текст джерелаSagiroglu, Serkan. "Adaptive Neural Network Applications On Missile Controller Design." Master's thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/3/12611106/index.pdf.
Повний текст джерелаa 5-Degree of Freedom (5-DOF) simulation model is obtained, and linearized at a single trim condition. An inverted model is used in the controller. Adaptive Neural Network (ANN) controllers namely, model inversion controllers with Sigma-Pi Neural Network, Single Hidden Layer Neural Network and Background Learning implemented Single Hidden Layer Neural Network, are deployed to cancel the modeling error and are applied for the longitudinal and directional channels of the missile. This approach simplifies the autopilot designing process by combining a controller with model inversion designed for a single flight condition with an on-line learning neural network to account for errors that are caused due to the approximate inversion. Simulations are performed both in the longitudinal and directional channels in order to demonstrate the effectiveness of the implemented control algorithms. The advantages and drawbacks of the implemented neural network based controllers are indicated.
Shahraeeni, Mohammad Sadegh. "Inversion of seismic attributes for petrophysical parameters and rock facies." Thesis, University of Edinburgh, 2011. http://hdl.handle.net/1842/4754.
Повний текст джерелаShin, Yoonghyun. "Neural Network Based Adaptive Control for Nonlinear Dynamic Regimes." Diss., Georgia Institute of Technology, 2005. http://hdl.handle.net/1853/7577.
Повний текст джерелаGosal, Gurpreet Singh. "The use of Inverse Neural Networks in the Fast Design of Printed Lens Antennas." Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/32249.
Повний текст джерелаSOUZA, MARCELO GOMES DE. "DETERMINISTIC ACOUSTIC SEISMIC INVERSION USING ARTIFICIAL NEURAL NETWORKS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2018. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=34647@1.
Повний текст джерелаCOORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
PROGRAMA DE EXCELENCIA ACADEMICA
A inversão sísmica é o processo de transformar dados de Sísmica de Reflexão em valores quantitativos de propriedades petroelásticas das rochas. Esses valores, por sua vez, podem ser correlacionados com outras propriedades ajudando os geocientistas a fazer uma melhor interpretação que resulta numa boa caracterização de um reservatório de petróleo. Existem vários algoritmos tradicionais para Inversão Sísmica. Neste trabalho revisitamos a Inversão Colorida (Impedância Relativa), a Inversão Recursiva, a Inversão Limitada em Banda e a Inversão Baseada em Modelos. Todos esses quatro algoritmos são baseados em processamento digital de sinais e otimização. O presente trabalho busca reproduzir os resultados desses algoritmos através de uma metodologia simples e eficiente baseada em Redes Neurais e na pseudo-impedância. Este trabalho apresenta uma implementação dos algoritmos propostos na metodologia e testa sua validade num dado sísmico público que tem uma inversão feita pelos métodos tradicionais.
Seismic inversion is the process of transforming Reflection Seismic data into quantitative values of petroleum rock properties. These values, in turn, can be correlated with other properties helping geoscientists to make a better interpretation that results in a good characterization of an oil reservoir.There are several traditional algorithms for Seismic Inversion. In this work we revise Color Inversion (Relative Impedance), Recursive Inversion, Bandwidth Inversion and Model-Based Inversion. All four of these algorithms are based on digital signal processing and optimization. The present work seeks to reproduce the results of these algorithms through a simple and efficient methodology based on Neural Networks and pseudo-impedance. This work presents an implementation of the algorithms proposed in the methodology and tests its validity in a public seismic data that has an inversion made by the traditional methods.
Thompson, Benjamin Berry. "Inversion and fast optimization using computational intelligence with applications to geoacoustics /." Thesis, Connect to this title online; UW restricted, 2004. http://hdl.handle.net/1773/5886.
Повний текст джерелаArtun, F. Emre. "Reservoir characterization using intelligent seismic inversion." Morgantown, W. Va. : [West Virginia University Libraries], 2005. https://eidr.wvu.edu/etd/documentdata.eTD?documentid=4185.
Повний текст джерелаTitle from document title page. Document formatted into pages; contains xii, 82 p. : ill. (some col.), maps (some col.). Includes abstract. Includes bibliographical references (p. 80-82).
Hardarson, Gisli. "The Effects of Using Results from Inversion by Evolutionary Algorithms to Retrain Artificial Neural Networks." Thesis, University of Skövde, Department of Computer Science, 2000. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-411.
Повний текст джерелаThe aim of inverting artificial neural networks (ANNs) is to find input patterns that are strongly classified as a predefined class. In this project an ANN is inverted by an evolutionary algorithm. The network is retrained by using the patterns extracted by the inversion as counter-examples, i.e. to classify the patterns as belonging to no class, which is the opposite of what the network previously did. The hypothesis is that the counter-examples extracted by the inversion will cause larger updates of the weights of the ANN and create a better mapping than what is caused by retraining using randomly generated counter-examples. This hypothesis is tested on recognition of pictures of handwritten digits. The tests indicate that this hypothesis is correct. However, the test- and training errors are higher when retraining using counter-examples, than for training only on examples of clean digits. It can be concluded that the counter-examples generated by the inversion have a great impact on the network. It is still unclear whether the quality of the network can be improved using this method.
Foddis, Maria Laura. "Application of artificial neural networks in hydrogeology : Identification of unknown pollution sources in contaminated aquifers." Strasbourg, 2011. https://publication-theses.unistra.fr/public/theses_doctorat/2011/FODDIS_Maria_Laura_2011.pdf.
Повний текст джерела[. . . ]In many cases, some hydrogeological and groundwater quality characteristics, are not directly measurable and must be physically assessed in function of directly measurable parameters. The problem of determining the unknown model parameters is usually identified as "inverse problem". Solving the inverse problem is the main goal of modeling groundwater flow and contaminant transport. The validity of an aquifer forecasting model is closely related to the reliability and accuracy of the parameters assessment. With respect to the resolution of the inverse problem, this work aims at defining a methodology that allows to identify the features in space and time of unknown contamination sources. In our case, the inverse problem is solved on the basis of measurements of contaminant concentrations in monitoring wells located in the studied areas. In the framework of this thesis, the research is developed under the following themes: - groundwater contamination modeling using a non-commercial software for the flux and transport model in porous media. - modeling of the cause and effect relationships in groundwater contamination with Artificial Neural Networks (ANN) technology. - application of ANN to solve the inverse problem in two cases of groundwater contamination. Over the past decades, Artificial Neural Networks (ANN) have become increasingly popular as a problem solving tool and have been extensively used as a forecasting tool in many disciplines. […]
Chen, Zhengxiao. "Microwave remote sensing of vegetation : Stochastic Lindenmayer systems, collective scattering effects, and neural network inversions /." Thesis, Connect to this title online; UW restricted, 1994. http://hdl.handle.net/1773/5854.
Повний текст джерелаFernandez, Cesar Aaron Moya. "Two alternative inversion techniques for the determination of seismic site response and propagation-path velocity structure : spectral inversion with reference events and neural networks." 京都大学 (Kyoto University), 2004. http://hdl.handle.net/2433/147831.
Повний текст джерелаSahebi, Mahmod Reza. "Understanding microwave backscattering of bare soils by using the inversion of surface parameters, neural networks and genetic algorithm." Thèse, Université de Sherbrooke, 2003. http://savoirs.usherbrooke.ca/handle/11143/2736.
Повний текст джерелаBoumaaza, Bouharket. "3D seismic attributes analysis and inversions for prospect evaluation and characterization of Cherokee sandstone reservoir in the Wierman field, Ness County, Kansas." Thesis, Kansas State University, 2017. http://hdl.handle.net/2097/35510.
Повний текст джерелаDepartment of Geology
Abdelmoneam Raef
Matthew W. Totten
This work focuses on the use of advanced seismically driven technologies to estimate the distribution of key reservoir properties which mainly includes porosity and hydrocarbon reservoir pay. These reservoir properties were estimated by using a multitude of seismic attributes derived from post-stack high resolution inversions, spectral imaging and volumetric curvature. A pay model of the reservoir in the Wierman field in Ness County, Kansas is proposed. The proposed geological model is validated based on comparison with findings of one blind well. The model will be useful in determining future drilling prospects, which should improve the drilling success over previous efforts, which resulted in only few of the 14 wells in the area being productive. The rock properties that were modeled were porosity and Gamma ray. Water saturation and permeability were considered, but the data needed were not available. Sequential geological modeling approach uses multiple seismic attributes as a building block to estimate in a sequential manner dependent petrophysical properties such as gamma ray, and porosity. The sequential modelling first determines the reservoir property that has the ability to be the primary property controlling most of the other subsequent reservoir properties. In this study, the gamma ray was chosen as the primary reservoir property. Hence, the first geologic model built using neural networks was a volume of gamma ray constrained by all the available seismic attributes. The geological modeling included post-stack seismic data and the five wells with available well logs. The post-stack seismic data was enhanced by spectral whitening to gain as much resolution as possible. Volumetric curvature was then calculated to determine where major faults were located. Several inversions for acoustic impedance were then applied to the post-stack seismic data to gain as much information as possible about the acoustic impedance. Spectral attributes were also extracted from the post-stack seismic data. After the most appropriate gamma ray and porosity models were chosen, pay zone maps were constructed, which were based on the overlap of a certain range of gamma ray values with a certain range of porosity values. These pay zone maps coupled with the porosity and gamma ray models explain the performance of previously drilled wells.
Gueye, Mbaye Babacar. "Inversion neuronale pour la reconstruction de profils de salinité océanique en Atlantique tropical à partir de mesures de surface et de hauteurs d'eau." Electronic Thesis or Diss., Paris 6, 2015. http://www.theses.fr/2015PA066743.
Повний текст джерелаWater exchanges within the global hydrological cycle are determined by complex constraints that form the basis of climate dynamics system.Ocean salinity (S) is one of the most delicate variables to monitor in this cycle. The in-situ measurements cover only limited resolutions. While surface measurements have good spatio- temporal coverage. In this thesis, we reconstruct ocean S profile in the tropical Atlantic from surface parameters (SSH-ADT, SST, SSS). The developed inversion model (INV2) comes in 2 parts. The exploratory part allowed to know that the latitude is related to the S of the subsurface and the depth while the SSS is linked to S of surface and near surface but not to the studied surface parameters. The latitude is strongly linked to the SSH (ADT) and the SST. Based on this preliminary study, we have implemented INV2 which is based on a sequential 3 steps algorithm (2 projections on a SOM and an optimal research). INV2 could reconstructed the S profiles simulated by the DRAKKAR model with mean absolute errors less than 0.08 psu on almost all the profile. With the in situ Coriolis data , the rmse are around 0.172 psu on individual profiles 0.037 psu on average profiles. The largest errors were noted at the halocline and in MSW areas. After the evaluation, a S profiles completion algorithm was also proposed. The INV2 performances obtained showed that this neural approach is adequate for 3D reconstruction of oceanic S when knowledge is limited to the surface
Smaili, Melik. "3-D seismic-based lithology prediction using impedance inversion and neural networks application: case-study from the Mannville Group in East-Central Alberta, Canada." Thesis, McGill University, 2009. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=67036.
Повний текст джерелаLa Formation Mannville (Crétacé Inférieur) du Centre Est de l'Alberta est l'un des principaux objectifs concernant l'exploration des hydrocarbures, typiquement associés à un contrôle stratigraphique. Les environnements de dépôts sont variés, allant du domaine fluvio-continental au domaine marin. Les dépôts de la Formation Mannville reposent sur une discordance stratigraphique majeure qui les sépare des dépôts carbonatés du Paléozoïque (Devonien). Nous avons cherché à intégrer des données de puits pour reconstituer l'architecture stratigraphique dans la zone d'étude. L'inversion sismique à été appliquée aux données existantes, et s'est trouvée être un excellent outil pour cartographier les discordances, faisant clairement la distinction entre les dépôts silico-clastiques des dépôts carbonatés en dessous. Les résultats de l'inversion ont ensuite été utilisés comme faisant partie des attributs sismiques appliqués au jeu de données dans le but de rechercher si la distribution des sédiments silici-clastiques dans la zone d'étude peut être distinguée d'un point de vu sismique. A travers une analyse de régression point par point, une combinaison de six attributs à fourni le meilleur jeu capable de prédire l'information lithologique dans les données sismiques dérivées des données de puits (Gamma-Ray). Ce résultat a été transféré dans un réseau de neurones, qui utilise cette relation pour s'entraîner à prédire la réponse du Gamma-Ray au delà des points de contrôle dans le volume sismique. Cela conduit à la génération d'un volume informé en pseudo-lithologie capable d'estimer la distribution de la lithologie à l'intérieur de le Formation Mannville sur l'ensemble de l'étude 3-D. Ce nouveau volume est capable de mettre en évidence les caractéristiques stratigraphiques invisibles avec l'amplitude sismique et dans les volumes d'inversion. Ce
Gagliardi, Raphael Luiz. "Aplicação de Inteligência Computacional para a Solução de Problemas Inversos de Transferência Radiativa em Meios Participantes Unidimensionais." Universidade do Estado do Rio de Janeiro, 2010. http://www.bdtd.uerj.br/tde_busca/arquivo.php?codArquivo=7543.
Повний текст джерелаThis research consists in the solution of the inverse problem of radiative transfer for a participating media (emmiting, absorbing and/or scattering) homogeneous one-dimensional in one layer, using the combination of artificial neural network (ANN), with optimization techniques. The output of the ANN, properly trained presents the values of the radiative properties [w, to, p1 e p2] that are optimized through the following techniques: Particle Collision Algorithm (PCA), Genetic Algorithm (GA), Greedy Randomized Adaptive Search Procedure (GRASP) and Tabu Search (TS). The data used in the training are synthetics, generated through the direct problem without the introduction of noise. The results obtained by the (ANN) alone, presents an average percentage error minor than 1,64%, what it would be satisfying, however, for the treatment using the four techniques of optimization aforementioned, the results have become even better with percentage errors minor than 0,03%, especially when the optimization is made by the GA.
Foudil-Bey, Nacim. "Développement d'outils d'interprétation de données géophysiques." Thesis, Université de Lorraine, 2012. http://www.theses.fr/2012LORR0142/document.
Повний текст джерелаIn recent years with the technology developments, airborne geophysical methods (gravity, magnetic, and electromagnetic) are widely used in the natural resource exploration at the regional scale. It covers large areas particularly in the areas with difficult access. The first part of this thesis consist on the development of new forward modeling algorithm for the calculation of the components of the gravity and magnetic fields based on a tetrahedron grid. The tetrahedral mesh allows the representation of very complex geological models holding many heterogeneous and faulted zones with an optimal number of elements, this reduces significantly the time calculation. Several inversion techniques use mathematical constraints for the resolution of the inverse problem in order to reduce the number of possible models. However the proposed solutions called also "the most probable model" provide a smooth solutions that cannot represent the geological reality. To circumvent this problem in the second and the third parts of this thesis, we made two major improvements. The first, we integrate Sequential Gaussian Simulation into the inversion procedure to determine a possible distributions of a single property. The second is that we used the Co-Simulation in the case of joint inversion to estimate a posteriori probabilities of the simulated models. The last part of this thesis presents an alternative to the several variables simulation, supervised learning of neural networks allows to establish a relationship between the different variables
Gil, Mauro Cesar Cantarino. "Aplicação de redes neuro-fuzzy para a solução de problemas inversos em transferência radiativa." Universidade do Estado do Rio de Janeiro, 2010. http://www.bdtd.uerj.br/tde_busca/arquivo.php?codArquivo=1605.
Повний текст джерелаIn this thesis is proposed an implementation for solving the inverse problem with the estimates of radiative properties (the single scattering albedo, the optical thickness of the media and the diffuse reflectivities) by the values of the intensities of radiation that leaves the participant medium using a hybrid approach of neuro-fuzzy systems, which combines the use of fuzzy inference systems with artificial neural networks. The use of this hybrid system try to include the ability of fuzzy systems in the treatment of inaccurate, imprecise, and vague data, and the ability of artificial neural networks to deal with learning from experience and widespread knowledge. Also is proposed a methodology for machines committees in neuro-fuzzy solution of this inverse problem in radiative transfer. It was observed in parallel that the solution of neuro-fuzzy systems and hybrid systems neuro-fuzzy committee machines, have a poor quality results when using the experimental data with the lowest sensitivity coefficients for the parameters that will be estimated. Moreover, when data are used with greater sensitivity, better results are obtained. This approach seeks to avoid the possibility of non-convergence in such methods.
Soares, Patricia Oliva. "Um problema inverso em dois passos para estimação de perfis de temperatura na atmosfera com nuvens a partir de medidas de radiância feitas por satélite." Universidade do Estado do Rio de Janeiro, 2013. http://www.bdtd.uerj.br/tde_busca/arquivo.php?codArquivo=4776.
Повний текст джерелаThis thesis presents a methodology for retrieving vertical temperature profiles in the atmosphere with clouds from radiance measurements made by satellite, using artificial neural networks. Vertical temperature profiles are important initial conditions for numerical weather prediction models, and are usually obtained from measurements of radiance using infrared channels. Though, when these measurements are performed in the atmosphere with clouds, it is not possible to retrieve the temperature profile with current techniques. It is a significant loss of information, since on average 20% of the pixels of the images have clouds. In this thesis, this problem is solved as a two-step inverse problem: the first step is an inverse problem of boundary condition estimation, where the radiance reaching the cloud basis is determined from radiance measured by satellite; the second step consists in determining the vertical temperature profile from the boundary condition estimated in the first step. Reconstructions of temperature profile are presented for four test cases. The results show that the proposed methodology produces satisfactory results and has great potential for use, allowing to incorporate information from a wider area of the planet and thus to improve numerical weather prediction models.
Corbí, Cabrera Adrián. "Estudio de redes neuronales y modelos de cuadripolos para la solución del problema inverso en ensayos no destructivos por medio de corrientes inducidas. Aplicación para el control de espesores en superficies metálicas con protección multicapa." Doctoral thesis, Universitat Politècnica de València, 2016. http://hdl.handle.net/10251/63448.
Повний текст джерела[ES] Estudio de redes neuronales y modelos de cuadripolos para la solución del problema inverso en ensayos no destructivos, por medio de corrientes inducidas. Aplicación para el control de espesores en superficies metálicas con protección multicapa Resumen En la actualidad el uso de métodos de prueba empleando ensayos de corrientes inducidas se ha generalizado en la industria, no sólo en el campo de los ensayos no destructivos, para estudiar el comportamiento de las grietas en elementos sujetos a fatiga así como para detectar fallas en la estructura interna metálica, sino también como instrumentos de medida para obtener información de la caracterización de los materiales, composición de las capas superficiales, magnitud de la oxidación superficial, espesor de las capas superficiales tratadas para su endurecimiento. Sin embargo, la aplicación de corrientes inducidas para conocer el dimensionado de capas superficiales puede resolverse mediante el problema directo pero no así el inverso, obtener a partir de las mediciones de parámetros electromagnéticos, las dimensiones de las capas estratificadas en la superficie del metal. Este caso singular es el que trata de resolver esta tesis de manera que empleando un modelado que sustituye las distintas capas físicas del material, por elementos cuadripolares o cuadripolos, de cuyo comportamiento se puede establecer el paralelismo con que aparecen las corrientes inducidas en la superficie del metal en condiciones reales. Para esto, se han tomado varios juegos de placas con distintos espesores conocidos y se han medido sus impedancias características mediante sensores adecuados. Los resultados obtenidos sirven para entrenar una red neuronal artificial, y por tanto deben de permitir su empleo para resolver el problema inverso, es decir, a partir de las lecturas de la medición como entrada de la red neuronal obtener las dimensiones buscadas a la salida. Los trabajos se inician con un estudio detallado de las soluciones a las ecuaciones de campos electromagnéticos armónicos y para el modelo que se propone. Se usa el método vectorial del potencial vector magnético con las condiciones de contraste de Coulomb. Se estudian la propagación de señales en las proximidades de la superficie y en la región frontera. Se establece la formulación básica de las corrientes inducidas y se estudian con detalle dos problemas concretos y sus modelos, el de una placa de espesor finito y el de un cilindro. Con todo ello se propone un método de resolución de las ecuaciones del problema mediante el empleo de series numéricas en la sustitución de las integrales con límite superior infinito. Se obtienen resultados para el cálculo de los parámetros resultantes en función de la frecuencia de ensayo y para un modelo establecido. Se propone un modelo de simulación ANSYS con dos soluciones, en la primera se emplea un modelo plano PLANE53 y en la segunda un modelo tridimensional SOLID236. A partir de este último se estudia la sensibilidad del ensayo de corrientes inducidas por comparación de resultados al modificar las condiciones del medio, permeabilidad y conductividad. También se propone un modelo de propagación de señal similar al de una línea de transmisión en telecomunicaciones, para ello se establecen modelos de cuadripolos y se conectan en cadena, los resultados teóricos se obtienen par las distintas frecuencias y sirven para mostrar un método de medida u control de los distintos espesores
[CAT] «Estudi de xarxes neuronals i models de quadripols per a la solució del problema invers en assajos no destructius, per mitjà de corrents induïts. Aplicació per al control de gruixos en superfícies metàl·liques amb protecció multicapa» Resum En l'actualitat l'ús de mètodes de prova emprant assaigs de corrents induïts s'ha generalitzat en la indústria, no només en el camp dels assajos no destructius, per estudiar el comportament de les esquerdes en elements subjectes a fatiga així com per detectar falles en l'estructura interna metàl·lica, sinó també com a instruments de mesura per obtenir informació de la caracterització dels materials, composició de les capes superficials, magnitud de l'oxidació superficial, espessor de les capes superficials tractades per al seu enduriment. No obstant això, l'aplicació de corrents induïts per conèixer el dimensionament de capes superficials pot resoldre mitjançant el problema directe però no així l'invers, obtenir a partir dels mesuraments de paràmetres electromagnètics, les dimensions de les capes estratificades en la superfície del metall. Aquest cas singular és el que tracta de resoldre aquesta tesi de manera que emprant un modelatge que substitueix les diferents capes físiques del material, per elements quadrupolars o quadripols, del comportament es pot establir el paral·lelisme amb què apareixen els corrents induïdes en la superfície del metall en condicions reals. Per això, s'han pres diversos jocs de plaques amb diferents gruixos coneguts i s'han mesurat les seves impedàncies característiques mitjançant sensors adequats. Els resultats obtinguts serveixen per entrenar una xarxa neuronal artificial, i per tant han de permetre la seva ocupació per resoldre el problema invers, és a dir, a partir de les lectures del mesurament com a entrada de la xarxa neuronal obtenir les dimensions buscades a la sortida. Els treballs s'inicien amb un estudi detallat de les solucions a les equacions de camps electromagnètics harmònics i per al model que es proposa. Es fa servir el mètode vectorial del potencial vector magnètic amb les condicions de contrast de Coulomb. S'estudien la propagació de senyals en les proximitats de la superfície hi ha la regió frontera. S'estableix la formulació bàsica dels corrents induïts i s'estudien amb detall dos problemes concrets i els seus models, el d'una placa de gruix finit i el d'un cilindre. Amb tot això es proposa un mètode de resolució de les equacions del problema mitjançant l'ús de sèries numèriques en la substitució de les integrals amb límit superior infinit. S'obtenen resultats per al càlcul dels paràmetres resultants en funció de la freqüència d'assaig i per a un model establert. Se proposa un model de simulació ANSYS amb dues solucions, en la primera es fa servir un model pla PLANE53 i en la segona un model tridimensional SOLID236. A partir d'aquest últim s'estudia la sensibilitat de l'assaig de corrents induïts per comparació de resultats en modificar les condicions del medi, permeabilitat i conductivitat. També es proposa un model de propagació de senyal similar al d'una línia de transmissió en telecomunicacions, per això s'estableixen models de quadripols i es connecten en cadena, els resultats teòrics s'obtenen bat les diferents freqüències i serveixen per mostrar un mètode de mesura o control dels diferents gruixos.
Corbí Cabrera, A. (2016). Estudio de redes neuronales y modelos de cuadripolos para la solución del problema inverso en ensayos no destructivos por medio de corrientes inducidas. Aplicación para el control de espesores en superficies metálicas con protección multicapa [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/63448
TESIS
Oliveira, Rogério Campos de. "Aplicação de máquinas de comitê de redes neurais artificiais na solução de um problema inverso em transferência radiativa." Universidade do Estado do Rio de Janeiro, 2010. http://www.bdtd.uerj.br/tde_busca/arquivo.php?codArquivo=1732.
Повний текст джерелаThis work is based on the concept of neural networks committee machine and has the objective to solve the inverse radiative transfer problem in one-dimensional, homogeneous, absorbing and isotropic scattering media. The artificial neural networks committee machine adds and combines the knowledge acquired by an exact number of specialists which are represented, individually, by each one of the artificial neural networks (ANN) that composes the artificial neural network committee machine. The aim is to reach a final result better than the one obtained by any of the artificial neural network separately, selecting only those artificial neural networks that presents the best results during the generalization phase and discarding the others, what was done in this present work. Here are used two static models of committee machines, using the ensemble arithmetic average, that differ between themselves only by the composition of the output combinator by each one of the committee machine. Are obtained, using artificial neural networks committee machines, estimates for the radiative transfer parameters, that is, medium optical thickness, single scattering albedo and diffuse reflectivities. Finally, the results obtained with both models of committee machine are compared between themselves and with those found using artificial neural networks type multi-layer perceptrons (MLP), isolated. Here that artificial neural networks are named as specialists neural networks, showing that the technique employed brings performance and results improvements with relatively low computational cost.
Kornrumpf, Luiz Henrique Damato. "Algoritmos de tratamento de curvas para determinação de parâmetros de geradores síncronos através do ensaio de resposta em frequência utilizando metodologia com inversor de frequência." Universidade de São Paulo, 2016. http://www.teses.usp.br/teses/disponiveis/3/3143/tde-08032017-085403/.
Повний текст джерелаThe frequency response test on synchronous generators has been increasing in recent decades, but the high cost of equipment used for conducting the test is still a stumbling block for both manufacturers and end-consumers. This dissertation aims to complement previous work, through the use of artificial neural networks to identify patterns in tests conducted with low-cost and low-resolution equipment. Through the artificial neural networks used it is possible to estimate a new set of test points without retesting is necessary or even a more expensive assay equipments. Through a combination of data processing algorithms, the approach tested models with theoretical models is possible and through these results to obtain electrical parameters of synchronous generators.
Lavergne, Fabien. "Méthodologie de synthèse de lois de commandes non-linéaires et robustes : application au suivi de trajectoire des avions de transport." Toulouse 3, 2005. http://www.theses.fr/2005TOU30248.
Повний текст джерелаThe work presented in this PhD thesis report is situated within the framework of the nonlinear and robust control of transport aircrafts. The purpose of this thesis is to couple the properties of nonlinear controllers (adaptation to the aircraft nonlinearities, explicit controllers synthesis, easy and decoupled setting once the synthesis is achieved, genericity of the obtained control laws) with essential robustness properties. Indeed, to guarantee the flight safety, both in manual handling and in automatic control, the control laws have to present strong robust stability and performances properties. After an introduction to the industrial and research context, a "techniques, methods and tools" part allows us to point out the thesis contributions in the nonlinear robust control and automatic modelling domains. The nonlinear robust control technique presented, called RMI control (for "Robust Multi-Inversion") is based on the now classical Nonlinear Dynamic Inversion (NDI) technique, notably studied at Airbus for some years (Fabrice VILLAUME, Jean DUPREZ), and is robustified by adding a complementary observation loop. We also present an automatic tool creating nonlinear, multivariable and embeddable models, as well as neural networks correlated methods. This tool is mandatory for the industrialization of our model-based flight control laws. Then the applicative part of the thesis underlines the specificities of the "aircraft" system and proposes flight control laws architectures, associated reference trajectories, and the advanced validation of the whole system by simulations performed on Airbus' certified simulator. Finally, after a conclusion on the main results and perspectives linked to the thesis, we propose annexes allowing to go further into the details of certain parts of our study
Huang, Shu-Chih, and 黃淑枝. "Inversion for Acoustic Impedance Using Artificial Neural Network." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/78971085414037241548.
Повний текст джерела國立成功大學
造船及船舶機械工程學系碩博士班
91
A new approach for measuring acoustic impedance is developed by using Artificial Neural Network(ANN) algorithm. Instead of using impedance tube, a rectangular room or a box is simulated with known boundary conditions at some boundaries and a unknown acoustic impedance at one side of the wall. The training data basis fort the ANN algorithm is evaluated by Similar Source Method which was developed earlier by Too[1999] for the estimation of interior and exterior sound field. The training data basis is constructed by evaluating of acoustic pressure at a field point with various acoustic impedance conditions at one side of the wall. The simulation result indicates that the prediction of acoustic impedance is very accurate with error percentage under 1%. Also, one point field measure-ment in the present approach provides a straightforward and easy evaluation than that in the two points measurement of the impedance tube approach.
Phan, Son Dang Thai. "Pre-injection reservoir evaluation at Dickman Field, Kansas." Thesis, 2011. http://hdl.handle.net/2152/ETD-UT-2011-08-3908.
Повний текст джерелаtext
Naidoo, Myrin Anand. "Nonlinear Control with State Estimation and Power Optimization for a ROM Ore Milling Circuit." Diss., 2015. http://hdl.handle.net/2263/44240.
Повний текст джерелаDissertation (MEng)--University of Pretoria, 2015.
Electrical, Electronic and Computer Engineering
Unrestricted
余勝棟. "Neural Networks and Genetic Algorithms for Well Logging Inversion." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/70700787165613620763.
Повний текст джерела國立交通大學
資訊學院碩士在職專班資訊組
95
In well logging inversion problem, a non-linear mapping exists between the synthetic logging measurements and the true formation conductivity. Without complexity of theoretic computation, neural network is able to approximate the input-output mapping through training with the iterative adjustment of connection weights. In our study, we develop the higher-order feature neural nets on the basis of neural network, and then apply on well logging inversion. The usually used training algorithm for neural network is gradient descent, which is easy to get trapped at local minimum, so we adopt a method that combine with genetic algorithm to improve the training efficiency. In addition, the convergence of gradient descent is slow, so we adopt the conjugate gradient to speed up the convergence. In order to make network more non-linear, we proposed higher-order feature neural nets that use functions to expand the input feature to higher degree. In order to use more training patterns and increase the convergence efficiency, we test various network architectures that use different number of input nodes. Besides, the experimental results show that the convergence efficiency of the network with 1 hidden layer is better than that without hidden layer, so we adopt the network with 1 hidden layer. We use 31 synthetic logging datasets. Each has 200 input features and corresponding outputs. The performance of network is evaluated by comparing the mean absolute error between the actual outputs and desired outputs. Leave-one-out validation method is used in experiments. Each time 30 datasets are used in training, the trained network is then tested with the left 1 dataset. After 31 trials, the network performance is computed by averaging these testing results. To validate the effectiveness of higher-order feature neural nets, the network size is 30-36-10 (not include bias), we train the network using conjugate gradient with synthetic logging datasets, and the trained network is then tested with real field logs. Results obtained from our experiments have shown that the proposed higher-order feature neural nets can be used effectively to process the well logging inversion. Our study shows an effective architecture of neural network to apply on well logging data inversion.
Chen, Chun-Yu, and 陳俊宇. "Higher Order Neural Networks and Differential Evolution for Well Log Data Inversion." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/91080441616213532424.
Повний текст джерела國立交通大學
資訊科學與工程研究所
96
Multilayer perceptron is adopted for well log data inversion. The gradient descent method is used in the back propagation learning rule and a hybrid method, which combines differential evolution (DE) and gradient descent method, are used in training process respectively. The input of the neural network is the apparent conductivity (Ca) of the well log and the desired output is the true formation conductivity (Ct). The higher order of the input features and the original features are the network input for training. From our experimental results, we find the expanding input features with back propagation learning rule can get fast convergence in training and decrease the mean absolute error between the desired output and the actual output. The hybrid method will provide more precise results, despite it takes a longer training time. The multilayer perceptron network, which is trained by the hybrid method, with 10 input features, the expanding input features to the third order, 8 hidden nodes, and 10 output nodes can get the smallest average mean absolute error on simulated well log data. And then the system is applied on the real well log data.
Василенко, Дмитро Олексійович. "Конструктивний синтез планарних антен природними алгоритмами оптимізації". Doctoral thesis, 2010. https://ela.kpi.ua/handle/123456789/641.
Повний текст джерелаNguyen, Tien Dat. "Vizualizace konceptů pomocí generování obrazu." Master's thesis, 2016. http://www.nusl.cz/ntk/nusl-346787.
Повний текст джерела