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Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)最新文献

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On taxonomy of evolutionary computation problems 论进化计算问题的分类学
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1331102
D. Ashlock, K. Bryden, S. Corns
{"title":"On taxonomy of evolutionary computation problems","authors":"D. Ashlock, K. Bryden, S. Corns","doi":"10.1109/CEC.2004.1331102","DOIUrl":"https://doi.org/10.1109/CEC.2004.1331102","url":null,"abstract":"Taxonomy is the practice of classifying members of a group based on their measurable characteristics. In evolutionary computation the problem of telling when two problems are similar is both challenging and important. An accurate classification technique would yield large benefits by permitting a researcher to rationally choose algorithm and parameter setting based on past experience. A good classification technique would also permit the selection of diverse test suites that would give a useful sense of the proper domain of application of a new technique. This study uses a standard taxonomic technique, hierarchical clustering, on a set of taxonomic characters derived from a comparative study using graph based evolutionary algorithms. The result is a cladogram that classifies the problems used in a reasonable fashion. Based on this we then argue that the technique given here can be used to provide an objective, automatic, extensible classification tool for any collection of evolutionary problems and discuss possible methods for improving the technique.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134014992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
A multicriteria genetic algorithm to analyze microarray data 一种多标准遗传算法分析微阵列数据
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1331124
Mohamed Khabzaoui, Clarisse Dhaenens, E. Talbi
{"title":"A multicriteria genetic algorithm to analyze microarray data","authors":"Mohamed Khabzaoui, Clarisse Dhaenens, E. Talbi","doi":"10.1109/CEC.2004.1331124","DOIUrl":"https://doi.org/10.1109/CEC.2004.1331124","url":null,"abstract":"Knowledge discovery from DNA microarray data has become an important research area for biologists. Association rules is an important task of knowledge discovery that can be applied to the analysis of gene expression in order to identify patterns of genes and regulatory network. Association rules discovery may be modeled as an optimization problem. We propose a multicriteria model for association rules problem and present a genetic algorithm designed to deal with association rules on DNA microarray data, in order to obtain associations between genes. Hence, we expose the main features of the proposed genetic algorithm. We emphasize on specificities for the association rule problem (encoding, mutation and crossover operators) and on its multicriteria aspects. Results are given for real datasets.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131784355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 21
Interactive exploratory data analysis 交互式探索性数据分析
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1330984
Sergey Malinchik, B. Orme, Joseph A. Rothermich, E. Bonabeau
{"title":"Interactive exploratory data analysis","authors":"Sergey Malinchik, B. Orme, Joseph A. Rothermich, E. Bonabeau","doi":"10.1109/CEC.2004.1330984","DOIUrl":"https://doi.org/10.1109/CEC.2004.1330984","url":null,"abstract":"We illustrate with two simple examples how interactive evolutionary computation (IEC) can be applied to exploratory data analysis (EDA). IEC is particularly valuable in an EDA context because the objective function is by definite either unknown a priori or difficult to formalize. The first example IEC is used to evolve the \"true\" metric of attribute space. Indeed, the assumed distance function in attribute space strongly conditions the information content of a two-dimensional display of the data, regardless of the dimension reduction approach. The goal here is to evolve the attribute space distance function until \"interesting\" features of the data are revealed when a clustering algorithm is applied. In a second example, we show how a user can interactively evolve an auditory display of cluster data. In this example, we use IEC with genetic programming to evolve a mapping of data to sound functions in order to sonify qualities of data clusters.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128939108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A hybrid intelligent system approach for improving the prediction of real world time series 一种用于改进真实世界时间序列预测的混合智能系统方法
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1330932
T. Ferreira, G. C. Vasconcelos, P. Adeodato
{"title":"A hybrid intelligent system approach for improving the prediction of real world time series","authors":"T. Ferreira, G. C. Vasconcelos, P. Adeodato","doi":"10.1109/CEC.2004.1330932","DOIUrl":"https://doi.org/10.1109/CEC.2004.1330932","url":null,"abstract":"This work presents a new procedure for the solution of time series forecasting problems which searches for the necessary minimum quantity of dimensions embedded in the problem for determining the characteristic phase space of the phenomenon generating the time series. The proposed system is inspired in F. Takens theorem (1980) and consists of an intelligent hybrid model composed of an artificial neural network (ANN) combined with a modified genetic algorithm (GA). It is shown how this proposed model can boost the performance of time series prediction of both artificially generated time series and real world time series from the financial market. An experimental investigation is conducted with the introduced method with five different relevant time series and the results achieved are discussed and compared with previous results found in the literature, showing the robustness of the proposed approach.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128942183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 13
A simple elitist genetic algorithm for constrained optimization 约束优化的简单精英遗传算法
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1330869
S. Venkatraman, G. Yen
{"title":"A simple elitist genetic algorithm for constrained optimization","authors":"S. Venkatraman, G. Yen","doi":"10.1109/CEC.2004.1330869","DOIUrl":"https://doi.org/10.1109/CEC.2004.1330869","url":null,"abstract":"In this paper we propose a novel approach for solving constrained optimization problems using genetic algorithms. The main emphasis of this algorithm is to be problem independent and to produce consistent results in terms of the quality of feasible solutions. The basic characteristic of this algorithm is the complete ignorance of the objective function till at least one feasible solution is found. The elitist scheme is used to assure consistent results and to help guide the stochastic search to the more fruitful regions of the parameter space. We have used rank based fitness assignment and have experimented with two ranking schemes. We have developed an empirical analysis and supporting experimental comparisons to favor one ranking scheme over the other. Irrespective of the ranking scheme used, our algorithm has performed well providing at least one feasible solution for every run of the algorithm and producing results that are comparable to the best published before.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130734564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 15
Multiobjective parsimony enforcement for superior generalisation performance 多目标简化执行，提高泛化性能
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1330841
Y. Bernstein, Xiaodong Li, V. Ciesielski, A. Song
{"title":"Multiobjective parsimony enforcement for superior generalisation performance","authors":"Y. Bernstein, Xiaodong Li, V. Ciesielski, A. Song","doi":"10.1109/CEC.2004.1330841","DOIUrl":"https://doi.org/10.1109/CEC.2004.1330841","url":null,"abstract":"Program Bloat - phenomenon of ever-increasing program size during a GP run - is a recognised and widespread problem. Traditional techniques to combat program bloat are program size limitations of parsimony pressure (penalty functions). These techniques suffer from a number of problems, in particular their reliance on parameters whose optimal values it is difficult to a priori determine. In this paper, we introduce POPE-GP, a system that makes use of the NSGA-II multiobjective evolutionary algorithm as an alternative, parameter-free technique for eliminating program bloat. We test it on a classification problem and find that while vastly reducing program size, it does improve generalisation performance.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133186537","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 23
A framework for evolving fuzzy rule 模糊规则演化的框架
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1331104
Jonatan Gómez
{"title":"A framework for evolving fuzzy rule","authors":"Jonatan Gómez","doi":"10.1109/CEC.2004.1331104","DOIUrl":"https://doi.org/10.1109/CEC.2004.1331104","url":null,"abstract":"This work presents a framework for genetic fuzzy rule based classifier. First, a classification problem is divided into several two-class problems following a fuzzy class binarization scheme; next, a fuzzy rule is evolved for each two-class problem using a Michigan iterative learning approach; finally, the evolved fuzzy rules are integrated using the fuzzy class binarization scheme. In particular, some encoding schemes are implemented following the proposed framework and their performance is compared. Experiments are conducted with different public available data sets.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134497346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Augmented negative selection algorithm with variable-coverage detectors 变覆盖检测器的增广负选择算法
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1330982
Zhou Ji, D. Dasgupta
{"title":"Augmented negative selection algorithm with variable-coverage detectors","authors":"Zhou Ji, D. Dasgupta","doi":"10.1109/CEC.2004.1330982","DOIUrl":"https://doi.org/10.1109/CEC.2004.1330982","url":null,"abstract":"An augmentation of negative selection algorithm is developed featuring detectors that have variable coverage. While the detectors can have different kinds of variable properties in the light of this concept, the paper mainly describes the experiments of variable-sized detectors in real-valued space. Effects of the two main control parameters, self radius and expected coverage, are discussed and experimented with both synthesized and real-world datasets. The approach improves efficiency and reliability without compromising the order of magnitude of complexity.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"45 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131318259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 61
Evolutionary control of Lsystem interpretation l系统解释的进化控制
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1331180
D. Ashlock, K. Bryden
{"title":"Evolutionary control of Lsystem interpretation","authors":"D. Ashlock, K. Bryden","doi":"10.1109/CEC.2004.1331180","DOIUrl":"https://doi.org/10.1109/CEC.2004.1331180","url":null,"abstract":"An Lsystem or Lindenmayer system consists of a grammar and an interpreter. The grammar contains an axiom, usually a short string that the grammar expands into a long, complex string. The interpreter then renders the string into an object. The first use of Lsystems was to provide morphological models of plants. In this exploratory initial study, we use an evolutionary algorithm to evolve interpreters for Lsystems. The interpreter is a graphics turtle. For a given L-system the evolutionary algorithm tunes the turtle's parameter to cause it to drive in a constrained area of the Cartesian plane. Multiple Lsystems and planar regions are given. In some cases a startlingly small number of optima are located indicating a relatively simple fitness landscape.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131857280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 9
Towards a bounded Pareto-coevolution archive 向着一个有限的帕累托共同进化档案
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1331190
E. Jong
{"title":"Towards a bounded Pareto-coevolution archive","authors":"E. Jong","doi":"10.1109/CEC.2004.1331190","DOIUrl":"https://doi.org/10.1109/CEC.2004.1331190","url":null,"abstract":"Convolution offers adaptive methods for the selection of tests used to evaluate individuals, but the resulting evaluation can be unstable. Recently, general archive-based coevolution methods have become available for which monotonic progress can be guaranteed. The size of these archives may grow indefinitely however, thus limiting their application potential. Here, we investigate how the size of an archive for Pareto-coevolution may be limited while maintaining reliability. The LAyered Pareto-Coevolution Archive (LAPCA) is presented, and investigated in experiments. LAPCA features a tunable degree of reliability, and is found to provide reliable progress in a difficult test problem while maintaining approximately constant archive sizes.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115668371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 36
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