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Dissertations / Theses on the topic 'Evolutionary computation applications'

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Published: 16 July 2024

Last updated: 31 July 2025

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1

Pridgeon, Carey. "Diverse applications of evolutionary computation in bioinformatics : hypermotifs and gene regulatory network inference." Thesis, University of Exeter, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.479210.

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2

Abraham, Ajith 1968. "Hybrid soft computing : architecture optimization and applications." Monash University, Gippsland School of Computing and Information Technology, 2002. http://arrow.monash.edu.au/hdl/1959.1/8676.

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3

Rahman, Izaz Ur. "Novel particle swarm optimization algorithms with applications in power systems." Thesis, Brunel University, 2016. http://bura.brunel.ac.uk/handle/2438/12219.

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Optimization problems are vital in physical sciences, commercial and finance matters. In a nutshell, almost everyone is the stake-holder in certain optimization problems aiming at minimizing the cost of production and losses of system, and also maximizing the profit. In control systems, the optimal configuration problems are essential that have been solved by various newly developed methods. The literature is exhaustively explored for an appropriate optimization method to solve such kind of problems. Particle Swarm Optimization is found to be one of the best among several optimization methods

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4

Kok, Jonathan. "Design methodologies and architectures of hardware-based evolutionary algorithms for aerospace optimisation applications on FPGAS." Thesis, Queensland University of Technology, 2014. https://eprints.qut.edu.au/72904/5/Jonathan_Kok_Thesis.pdf.

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This thesis is a study of new design methods for allowing evolutionary algorithms to be more effectively utilised in aerospace optimisation applications where computation needs are high and computation platform space may be restrictive. It examines the applicability of special hardware computational platforms known as field programmable gate arrays and shows that with the right implementation methods they can offer significant benefits. This research is a step forward towards the advancement of efficient and highly automated aircraft systems for meeting compact physical constraints in aerospac

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5

Ranjeet, Tirtha. "Coevolutionary algorithms for the optimization of strategies for red teaming applications." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2012. https://ro.ecu.edu.au/theses/558.

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Red teaming (RT) is a process that assists an organization in finding vulnerabilities in a system whereby the organization itself takes on the role of an “attacker” to test the system. It is used in various domains including military operations. Traditionally, it is a manual process with some obvious weaknesses: it is expensive, time-consuming, and limited from the perspective of humans “thinking inside the box”. Automated RT is an approach that has the potential to overcome these weaknesses. In this approach both the red team (enemy forces) and blue team (friendly forces) are modelled as inte

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6

Creaser, Paul. "Application of evolutionary computation techniques to missile guidance." Thesis, Cranfield University, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.367124.

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7

Sharifi, Soroosh. "Application of evolutionary computation to open channel flow modelling." Thesis, University of Birmingham, 2009. http://etheses.bham.ac.uk//id/eprint/478/.

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This thesis examines the application of two evolutionary computation techniques to two different aspects of open channel flow. The first part of the work is concerned with evaluating the ability of an evolutionary algorithm to provide insight and guidance into the correct magnitude and trend of the three parameters required in order to successfully apply a quasi 2D depth averaged Reynolds Averaged Navier Stokes (RANS) model to the flow in prismatic open channels. The RANS modeled adopted is the Shiono Knight Method (SKM) which requires three input parameters in order to provide closure, i.e. t

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8

Hayward, Kevin. "Application of evolutionary algorithms to engineering design." University of Western Australia. School of Mechanical Engineering, 2008. http://theses.library.uwa.edu.au/adt-WU2009.0018.

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The efficiency of the mechanical design process can be improved by the use of evolutionary algorithms. Evolutionary algorithms provide a convenient and robust method to search for appropriate design solutions. Difficult non-linear problems are often encountered during the mechanical engineering design process. Solutions to these problems often involve computationally-intensive simulations. Evolutionary algorithms tuned to work with a small number of solution iterations can be used to automate the search for optimal solutions to these problems. An evolutionary algorithm was designed to give rel

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9

Wiltshire, Serge William. "On The Application Of Computational Modeling To Complex Food Systems Issues." ScholarWorks @ UVM, 2019. https://scholarworks.uvm.edu/graddis/1077.

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Transdisciplinary food systems research aims to merge insights from multiple fields, often revealing confounding, complex interactions. Computational modeling offers a means to discover patterns and formulate novel solutions to such systems-level problems. The best models serve as hubs—or boundary objects—which ground and unify a collaborative, iterative, and transdisciplinary process of stakeholder engagement. This dissertation demonstrates the application of agent-based modeling, network analytics, and evolutionary computational optimization to the pressing food systems problem areas of live

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10

Antão, Tiago Rodrigues. "Evolutionary applications of population genetics with a focus on malaria : a computational approach." Thesis, University of Liverpool, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.569901.

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Malaria is a major public health concern for the one-third of the human population esti- mated to be exposed to the threat of the most virulent species, Plasmodium falciparum. Modern molecular and computational tools from population genetics may help to better understand and fight the burden of drug resistant malaria. Malaria biology is substantially different from the underlying paradigm of standard population genetics models, most notably because malaria has both a asexual haploid phase and a sexual diploid phase where selfing (i.e. mating between genetically identical parasites) is possible

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11

Collins, Trevor. "The application of software visualization technology to evolutionary computation : a case study in Genetic Algorithms." Thesis, Open University, 1998. http://oro.open.ac.uk/28579/.

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Evolutionary computation is an area within the field of artificial intelligence that is founded upon the principles of biological evolution. Evolution can be defined as the process of gradual development. Evolutionary algorithms are typically applied as a generic problem solving method, searching a problem space in order to locate good solutions. These solutions are found through an iterative evolutionary search that progresses by means of gradual developments. In the majority of cases of evolutionary computation the user is not aware of their algorithm's search behaviour. This causes two prob

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12

Fabritius, Björn. "Application of genetic algorithms to problems in computational fluid dynamics." Thesis, University of Exeter, 2014. http://hdl.handle.net/10871/15236.

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In this thesis a methodology is presented to optimise non–linear mathematical models in numerical engineering applications. The method is based on biological evolution and uses known concepts of genetic algorithms and evolutionary compu- tation. The working principle is explained in detail, the implementation is outlined and alternative approaches are mentioned. The optimisation is then tested on a series of benchmark cases to prove its validity. It is then applied to two different types of problems in computational engineering. The first application is the mathematical modeling of turbulence.

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13

Luitel, Bipul. "Applications of swarm, evolutionary and quantum algorithms in system identification and digital filter design." Diss., Rolla, Mo. : Missouri University of Science and Technology, 2009. http://scholarsmine.mst.edu/thesis/pdf/Luitel_09007dcc805cd792.pdf.

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Thesis (M.S.)--Missouri University of Science and Technology, 2009.<br>Vita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed January 22, 2009) Includes bibliographical references (p. 135-137).

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14

Armstrong, Kathryn Anne. "Computational structure-based modeling and analysis with application to rational and evolutionary molecular engineering." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/39844.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Biological Engineering Division, 2007.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Includes bibliographical references (leaves 112-127).<br>The design and development of new proteins and small molecules has considerable practical application in medicine, industry, and basic science. Frequently, progress in this area is made by altering an existing small molecule or protein for new function. This thesis presents methods for the anal

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15

Morrison, Kevin S. "Topological Data Analysis and Applications to Influenza." Miami University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=miami1595864809447239.

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16

Zemzami, Maria. "Variations sur PSO : approches parallèles, jeux de voisinages et applications Application d’un modèle parallèle de la méthode PSO au problème de transport d’électricité A modified Particle Swarm Optimization algorithm linking dynamic neighborhood topology to parallel computation An evolutionary hybrid algorithm for complex optimization problems Interoperability optimization using a modified PSO algorithm A comparative study of three new parallel models based on the PSO algorithm Optimization in collaborative information systems for an enhanced interoperability network." Thesis, Normandie, 2019. http://www.theses.fr/2019NORMIR11.

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Reconnue depuis de nombreuses années comme une méthode efficace pour la résolution de problèmes difficiles, la méta-heuristique d’optimisation par essaim de particules PSO (Particle Swarm Optimization) présente toutefois des inconvénients dont les plus étudiés sont le temps de calcul élevé et la convergence prématurée. Cette thèse met en exergue quelques variantes de la méthode PSO visant à échapper à ces deux inconvénients de la méthode. Ces variantes combinent deux approches : la parallélisation de la méthode de calcul et l’organisation de voisinages appropriés pour les particules. L’évaluat

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17

Wijns, Christopher P. "Exploring conceptual geodynamic models : numerical method and application to tectonics and fluid flow." University of Western Australia. School of Earth and Geographical Sciences, 2005. http://theses.library.uwa.edu.au/adt-WU2005.0068.

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Geodynamic modelling, via computer simulations, offers an easily controllable method for investigating the behaviour of an Earth system and providing feedback to conceptual models of geological evolution. However, most available computer codes have been developed for engineering or hydrological applications, where strains are small and post-failure deformation is not studied. Such codes cannot simultaneously model large deformation and porous fluid flow. To remedy this situation in the face of tectonic modelling, a numerical approach was developed to incorporate porous fluid flow into an exist

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18

Vera-Licona, Martha Paola. "Algorithms for modeling and simulation of biological systems; applications to gene regulatory networks." Diss., Virginia Tech, 2007. http://hdl.handle.net/10919/28073.

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Systems biology is an emergent field focused on developing a system-level understanding of biological systems. In the last decade advances in genomics, transcriptomics and proteomics have gathered a remarkable amount data enabling the possibility of a system-level analysis to be grounded at a molecular level. The reverse-engineering of biochemical networks from experimental data has become a central focus in systems biology. A variety of methods have been proposed for the study and identification of the systemâ s structure and/or dynamics. The objective of this dissertation is to introduce

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19

Gunes, Baydin Atilim. "Evolut ionary adap tat ion in cas e - bas ed reasoning. An application to cross-domain analogies for mediation." Doctoral thesis, Universitat Autònoma de Barcelona, 2013. http://hdl.handle.net/10803/129294.

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L'analogia juga un papel fonamental en la resolucio de problemes i es troba darrere de molts dels processos centrals de la capacitat cognitiva humana, fins al punt que s'ha considerat "el nucli del coneixement". El raonament analogic funciona a traves del proces de la transferencia, l'us del coneixement apres en una situacio en l'altra per a la qual no va ser destinat. El paradigma de raonament basat en casos (case-based reasoning, CBR) presenta un model molt relacionat, pero lleugerament diferent de raonament utilitzat principalment en la intel.ligencia artificial; diferent en part perque el

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20

Wang, Chien-Tao, and 王建道. "The applications of evolutionary computation to the design of digital filter." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/34405488218469634016.

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碩士<br>樹德科技大學<br>資訊工程學系<br>94<br>In this thesis, two evolutionary computation algorithm, genetic algorithm (GA) and differential evolution (DE), are applied to the design of IIE filter. First, we use GA to design a Canonical Signed-Digit (CSD) code based IIR filter. It can be seen that, are to the special configuration of CSD code, GA is a better algorithm to evolve the CSD coded parameters. Second, an criterion for checking the stability of an IIR filter will be derived. The stability criterion is a base of designing stable IIR filter in this thesis. Finally, the two algorithms, GA and DE, are

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21

(20390), Baolin Wu. "Evolutionary strategies for function optimization, fuzzy modeling and control." Thesis, 2001. https://figshare.com/articles/thesis/Evolutionary_strategies_for_function_optimization_fuzzy_modeling_and_control/26309032.

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<p dir="ltr">Solving complex problems with evolutionary approaches has attracted increasing attention in recent years. The main advantage of such problem solving strategy is its robustness and ability to adapt to an unknown environment without explicit assumptions. </p><p dir="ltr">The aim of this thesis is to investigate evolutionary computation techniques and their applications in addressing three different problems - global function optimization, fuzzy modeling and control. We start by introducing the pertinent necessary background of evolutionary algorithms, and this is followed by a discu

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22

"Applications of evolutionary algorithms on biomedical systems." 2007. http://library.cuhk.edu.hk/record=b5893179.

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Tse, Sui Man.<br>Thesis (M.Phil.)--Chinese University of Hong Kong, 2007.<br>Includes bibliographical references (leaves 95-104).<br>Abstracts in English and Chinese.<br>Abstract --- p.i<br>Acknowledgement --- p.v<br>Chapter 1 --- Introduction --- p.1<br>Chapter 1.1 --- Motivation --- p.1<br>Chapter 1.1.1 --- Basic Concepts and Definitions --- p.2<br>Chapter 1.2 --- Evolutionary Algorithms --- p.5<br>Chapter 1.2.1 --- Chromosome Encoding --- p.6<br>Chapter 1.2.2 --- Selection --- p.7<br>Chapter 1.2.3 --- Crossover --- p.9<br>Chapter 1.2.4 --- Mutation --- p.10<br>Chapter 1.2.5 --- El

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23

Tiwari, A., J. Knowles, E. Avineri, Keshav P. Dahal, and R. Roy. "Applications of Soft Computing." 2006. http://hdl.handle.net/10454/2291.

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24

Bourennani, Farid. "Leadership based multi-objective optimization with applications in energy systems." Diss., 2013. http://hdl.handle.net/10155/396.

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Multi-objective optimization metaheuristics (MOMs) are powerful methods for solving complex optimization problems but can require a large number of function evaluations to find optimal solutions. Thus, an efficient multi-objective optimization method should generate accurate and diverse solutions in a timely manner. Improving MOMs convergence speed is an important and challenging research problem which is the scope of this thesis. This thesis conducted the most comprehensive comparative study ever in MOMs. Based on the results, multi-objective (MO) versions of particle swarm optimization (PSO)

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25

(11073474), Bin Zhang. "Data-driven Uncertainty Analysis in Neural Networks with Applications to Manufacturing Process Monitoring." Thesis, 2021.

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<p>Artificial neural networks, including deep neural networks, play a central role in data-driven science due to their superior learning capacity and adaptability to different tasks and data structures. However, although quantitative uncertainty analysis is essential for training and deploying reliable data-driven models, the uncertainties in neural networks are often overlooked or underestimated in many studies, mainly due to the lack of a high-fidelity and computationally efficient uncertainty quantification approach. In this work, a novel uncertainty analysis scheme is developed. The Gaussi

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26

"Learning Bayesian networks using evolutionary computation and its application in classification." 2001. http://library.cuhk.edu.hk/record=b5890754.

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by Lee Shing-yan.<br>Thesis (M.Phil.)--Chinese University of Hong Kong, 2001.<br>Includes bibliographical references (leaves 126-133).<br>Abstracts in English and Chinese.<br>Chapter 1 --- Introduction --- p.1<br>Chapter 1.1 --- Problem Statement --- p.4<br>Chapter 1.2 --- Contributions --- p.4<br>Chapter 1.3 --- Thesis Organization --- p.5<br>Chapter 2 --- Background --- p.7<br>Chapter 2.1 --- Bayesian Networks --- p.7<br>Chapter 2.1.1 --- A Simple Example [42] --- p.8<br>Chapter 2.1.2 --- Formal Description and Notations --- p.9<br>Chapter 2.1.3 --- Learning Bayesian Network from Dat

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27

Yi-HungTang and 湯伊鴻. "Application of Evolutionary Computation to the Design of Linear Antenna Arrays." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/28318885913704215209.

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28

(9813641), Dujuan Li. "Constrained multi-objective particle swarm optimization with application in power generation." Thesis, 2009. https://figshare.com/articles/thesis/Constrained_multi-objective_particle_swarm_optimization_with_application_in_power_generation/16910656.

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This thesis is devoted to the study of metaheuristic optimization algorithms and their application in power generation. The study focuses on constrained multi-objective optimization using Particle Swarm Optimization algorithm. A multi-objective constraint-handling method incorporating a dynamic neighbourhood PSO algorithm is proposed for tackling single objective constrained optimization problems. The benchmark simulation results demonstrate the proposed approach is effective and efficient in finding the consistent quality solutions. Compared with the recent research results, the proposed appr

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29

Chen, Zhen-Yao, and 陳振耀. "Application of Evolutionary Computation-Based Radial Basis Function Neural Network to IPC Sales Forecasting." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/d83vya.

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博士<br>國立臺北科技大學<br>工商管理研究所<br>98<br>Forecasting is one of the crucial factors in practical application since it ensures the effective allocation of capacity and proper amount of inventory. Since auto-regressive integrated moving average (ARIMA) models which are more suitable for linear data have their constraints in predicting complex data for the real-world problems, some approaches have been developed to conquer the challenge of nonlinear forecasting. Therefore, for the purpose of forecasting nonlinear data, this study intends to develop three integrated evolutionary computation (EC)-based al

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30

Xie, Yue. "Bio-Inspired Computing for Chance-Constrained Combinatorial Optimisation Problems." Thesis, 2021. https://hdl.handle.net/2440/134213.

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Bio-inspired methods have been widely used to solve stochastic optimisation problems, and they can find high-quality solutions. Motivated by real-world applications such as mining engineering problems where constraint violations have distributive effects, we discuss using chance-constrained optimisation to solve optimisation problems under various uncertainties. This thesis contributes to the theoretical analysis and application of evolutionary algorithms on chance-constrained combinatorial optimisation problems. We address complex problems under stochastic settings and are subject to chance c

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31

Chang, Che-Ming, and 張哲銘. "Application of real-coding on evolutionary computation for distribution system feeder reconfiguration problems under load variations." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/77c8x9.

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碩士<br>國立臺北科技大學<br>自動化科技研究所<br>100<br>As the concepts of environmental protection and energy saving bring more attention, how to reduce the energy loss during the normal operations of distribution system becomes an important issue. Feeder reconfiguration is a very important technique that can be used to deal with different types of distribution system problems. By changing the distribution system structure the distribution system can be operated in a more efficient way during normal and contingency operations. Feeder reconfiguration is a typical combinatorial optimization problem. Due to the la

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32

Sun, Yuan Ming, and 孫院明. "The Evaluation and Application of Constructing Investment Decision Model of Multi-Stages Based on Evolutionary Computation." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/98674956673234952877.

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碩士<br>輔仁大學<br>資訊管理學系<br>95<br>The real stock price is difficult to predict, so if can find out the relation of the financial value of every company and stock price, it will contributes to promoting accuracy predicted that the stock price fluctuates. The research designs the first stage model with ' Genetic Algorithms ' (GA), and designs the fitness function with ' Regression Analysis '. It succeeds in filtering 86 key indicators base on 605 items of stock financial indicator that Taiwan Economic Journal (TEJ) offer. There are obvious relations between it and stock price change. 　　And then acco

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McNeany, Scott Edward. "Characterizing software components using evolutionary testing and path-guided analysis." 2013. http://hdl.handle.net/1805/3775.

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Indiana University-Purdue University Indianapolis (IUPUI)<br>Evolutionary testing (ET) techniques (e.g., mutation, crossover, and natural selection) have been applied successfully to many areas of software engineering, such as error/fault identification, data mining, and software cost estimation. Previous research has also applied ET techniques to performance testing. Its application to performance testing, however, only goes as far as finding the best and worst case, execution times. Although such performance testing is beneficial, it provides little insight into performance characteristics o

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(9811760), Scott Ladley. "An investigation into the application of evolutionary algorithms on highly constrained optimal control problems and the development of a graphical user interface for comprehensive algorithm control and monitoring." Thesis, 2003. https://figshare.com/articles/thesis/An_investigation_into_the_application_of_evolutionary_algorithms_on_highly_constrained_optimal_control_problems_and_the_development_of_a_graphical_user_interface_for_comprehensive_algorithm_control_and_monitoring/19930160.

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<p>In this thesis we investigate how intelligent techniques, such as Evolutionary Algorithms, can be applied to finding solutions to discrete optimal control problems. Also, a detailed investigation is carried out into the design and development of a superior execution environment for Evolutionary Algorithms.</p> <p>An overview of the basic processes of an Evolutionary Algorithm is given, as well as detailed descriptions for several genetic operators. Several additional operators that may be applied in conjunction with an Evolutionary Algorithm are also studied. These operators include several

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