Evolutionary Optimization Methods
Mostrando 1-12 de 38 artigos, teses e dissertações.
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1. Photoacoustic-based thermal image formation and optimization using an evolutionary genetic algorithm
Abstract Introduction For improved efficiency and security in heat application during hyperthermia, it is important to monitor tissue temperature during treatments. Photoacoustic (PA) pressure wave amplitude has a temperature dependence given by the Gruenesein parameter. Consequently, changes in PA signal amplitude carry information about temperature varia
Res. Biomed. Eng.. Publicado em: 28/05/2018
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2. Energy Efficient Clustering in Multi-hop Wireless Sensor Networks Using Differential Evolutionary MOPSO
ABSTRACT The primary challenge in organizing sensor networks is energy efficacy. This requisite for energy efficacy is because sensor nodes capacities are limited and replacing them is not viable. This restriction further decreases network lifetime. Node lifetime varies depending on the requisites expected of its battery. Hence, primary element in constructi
Braz. arch. biol. technol.. Publicado em: 23/01/2017
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3. Developing and Multi-Objective Optimization of a Combined Energy Absorber Structure Using Polynomial Neural Networks and Evolutionary Algorithms
Abstract In this study a newly developed thin-walled structure with the combination of circular and square sections is investigated in term of crashworthiness. The results of the experimental tests are utilized to validate the Abaqus/ExplicitTM finite element simulations and analysis of the crush phenomenon. Three polynomial meta-models based on the evolved
Lat. Am. j. solids struct.. Publicado em: 2016
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4. Algoritmos para o custo médio a longo prazo de sistemas com saltos markovianos parcialmente observados / Algorithms for the long run average cost for linear systems with partially observed Markov jump parameters
In this work we are interested in the optimal control for the long run average cost (LRAC) problem for linear systems with Markov jump parameters (LSMJP), using heuristic methods like first generation evolutionary algorithms - genetic algorithm (GA) - and second generation algorithms including UMDA (Univariate Marginal Distribution Algorithm) and BOA (Bayesi
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 13/08/2012
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5. Estimação e previsão da estrutura a termo das taxas de juros usando técnicas de inteligência computacional / Term structure of interest rate modeling and forecasting using computational intelligence techniques
This work proposes the term structure of interest rates modeling and forecasting using computational intelligence techniques, based on data from the US and Brazilian fixed income markets. The yield curve modeling includes the use of some evolutionary computation methods like Genetic Algorithms, Differential Evolution and Evolution Strategies in comparison wi
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 25/06/2012
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6. Desenvolvimento de modelos e algoritmos sequenciais e paralelos para o planejamento da expansão de sistemas de transmissão de energia elétrica / Development of mathematical models, sequential and parallel algorithms for transmission expansion planning
The main objective of this study is to propose a new methodology to deal with the long-term transmission system expansion planning with multiple generation dispatch scenarios problem (TEP-MDG). With the methodology proposed in this thesis we aim to build expansion plans with minimum investment cost and also capable of meeting the new demands of modern electr
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 16/03/2012
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7. Application of an iterative method and an evolutionary algorithm in fuzzy optimization
This work develops two approaches based on the fuzzy set theory to solve a class of fuzzy mathematical optimization problems with uncertainties in the objective function and in the set of constraints. The first approach is an adaptation of an iterative method that obtains cut levels and later maximizes the membership function of fuzzy decision making using t
Pesqui. Oper.. Publicado em: 28/06/2012
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8. A new method for decision making in multi-objective optimization problems
Many engineering sectors are challenged by multi-objective optimization problems. Even if the idea behind these problems is simple and well established, the implementation of any procedure to solve them is not a trivial task. The use of evolutionary algorithms to find candidate solutions is widespread. Usually they supply a discrete picture of the non-domina
Pesqui. Oper.. Publicado em: 21/06/2012
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9. Aplicação de computação natural ao problema de estimação de direção de chegada / Application of natural computing to the problem of estimating the direction of arrival
O problema de estimação de direção de chegada (DOA, em inglês direction of arrival ) de ondas planas que incidem sobre um arranjo linear uniforme de sensores, através do critério da máxima verossimilhança (ML, em inglês maximum likelihood), requer a minimização de uma função custo não-linear, não-quadrática, multimodal e variante com a rela�
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 12/07/2010
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10. Parallel evolutionary algorithm to the sonet/sdh ring assigment problem / Algoritmo evolutivo paralelo para o problema de atribuição de localidades a anéis em redes sonet/sdh
The telecommunications play a fundamental role in the contemporary society, having as one of its main roles to give people the possibility to connect them and integrate them into society in which they operate and, therewith, accelerate development through knowledge. But as new technologies are introduced on the market, increases the demand for new products a
Publicado em: 2010
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11. Técnicas de otimização evolutiva aplicadas à solução de grandes sistemas lineares / Evolutionary Optimization Techniques Applied to Solution of Large Linear Systems
Muitos campos da engenharia e outras ciências aplicadas exigem a utilização da solução de sistemas lineares algébricos. Dependendo do modelo matemático usado para representar o fenômeno, os sistemas lineares são de elevada dimensão. Tradicionalmente, os grandes sistemas lineares são resolvidos através de métodos iterativos. A convergência deste
Publicado em: 2010
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12. Genetic programming: crossover operators, building blocks and semantic emergence / Programação genética: operadores de crossover, blocos construtivos e emergência semântica
Evolutionary algorithms are heuristic methods used to find solutions to optimization problems. These methods use stochastic search mechanisms inspired by Natural Selection Theory. Genetic Algorithms and Genetic Programming are two of the most popular evolutionary algorithms. These techniques make intensive use of crossover operators, a mechanism responsible
Publicado em: 2010