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

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Co-evolutionary particle swarm optimization for min-max problems using Gaussian distribution 基于高斯分布的最小-最大问题的协同进化粒子群优化
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1330965
R. Krohling, F. Hoffmann, L. Coelho
{"title":"Co-evolutionary particle swarm optimization for min-max problems using Gaussian distribution","authors":"R. Krohling, F. Hoffmann, L. Coelho","doi":"10.1109/CEC.2004.1330965","DOIUrl":"https://doi.org/10.1109/CEC.2004.1330965","url":null,"abstract":"Previous work presented an approach based on coevolutionary particle swarm optimization (Co-PSO) to solve constrained optimization problems formulated as min-max problems. Preliminary results demonstrated that Co-PSO constitutes a promising approach to solve constrained optimization problems. However the difficulty to obtain fine tuning of the solution using a uniform distribution became evident. In this paper, a modified PSO using a Gaussian distribution is applied in the context of Co-PSO. The modified Co-PSO is tested on some benchmark optimization problems and the results show a superior performance compared to the standard Co-PSO.","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":"116030640","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: 65
Finding multi-objective paths in stochastic networks: a simulation-based genetic algorithm approach 随机网络中寻找多目标路径:一种基于模拟的遗传算法方法
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1330854
Z. Ji, A. Chen, K. Subprasom
{"title":"Finding multi-objective paths in stochastic networks: a simulation-based genetic algorithm approach","authors":"Z. Ji, A. Chen, K. Subprasom","doi":"10.1109/CEC.2004.1330854","DOIUrl":"https://doi.org/10.1109/CEC.2004.1330854","url":null,"abstract":"Path finding is a fundamental research topic in transportation due to its wide applications in transportation planning and intelligent transportation system (ITS). In transportation, the path finding problem is usually defined as the shortest path (SP) problem in terms of distance, time, cost, or a combination of criteria under a deterministic environment. However, in real life situations, the environment is often uncertain. In this paper, we develop a simulation-based genetic algorithm to find multi-objective paths in stochastic networks. Numerical experiments are presented to demonstrate the algorithm feasibility.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"217 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":"122832069","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
Use of clustering to improve the layout of gene network for visualization 利用聚类技术改进基因网络布局，实现可视化
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1331151
N. Noman, Kouichi Okada, N. Hosoyama, H. Iba
{"title":"Use of clustering to improve the layout of gene network for visualization","authors":"N. Noman, Kouichi Okada, N. Hosoyama, H. Iba","doi":"10.1109/CEC.2004.1331151","DOIUrl":"https://doi.org/10.1109/CEC.2004.1331151","url":null,"abstract":"A very effective means to study the gene networks is visualization. With rapid increase of the size of gene networks, it has become more realistic to identify the collaborating genes in the network, which will facilitate the behavioral study of the groups and the network as a whole. In our previous paper, we presented a layered approach for visualizing gene regulatory networks. In this paper, we present a 3D layout model for visualizing gene networks, which clusters the correlated genes depending on their causal relationships. To demonstrate the effectiveness of the approach, we visualize real gene networks of different sizes. The experimental results show the superiority and usefulness of the new model when compared with previous results.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"2 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":"129854935","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: 2
Setting up performance surface of an artificial neural network with genetic algorithm optimization: in search of an accurate and profitable prediction of stock trading 利用遗传算法优化建立人工神经网络的性能面，寻求对股票交易进行准确、有利的预测
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1330963
Serge Hayward
{"title":"Setting up performance surface of an artificial neural network with genetic algorithm optimization: in search of an accurate and profitable prediction of stock trading","authors":"Serge Hayward","doi":"10.1109/CEC.2004.1330963","DOIUrl":"https://doi.org/10.1109/CEC.2004.1330963","url":null,"abstract":"This paper considers a design framework of a computational experiment in finance. The examination of relationships between statistics used for economic forecasts evaluation and profitability of investment decisions reveals that only the 'degree of improvement over efficient prediction' shows robust links with profitability. If profits are not observable, this measure is proposed as an evaluation criterion for an economic prediction. Also combined with directional accuracy, it could be used in an estimation technique for economic behavior, as an alternative to conventional least squares. Model discovery and performance surface optimization with genetic algorithm demonstrate profitability improvement with an inconclusive effect on statistical criteria.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"35 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":"123418519","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
Nonlinear system identification based on evolutionary fuzzy modeling 基于进化模糊模型的非线性系统辨识
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1330919
T. Hatanaka, Yoshio Kawaguchi, K. Uosaki
{"title":"Nonlinear system identification based on evolutionary fuzzy modeling","authors":"T. Hatanaka, Yoshio Kawaguchi, K. Uosaki","doi":"10.1109/CEC.2004.1330919","DOIUrl":"https://doi.org/10.1109/CEC.2004.1330919","url":null,"abstract":"The local modeling such as TSK fuzzy modeling is well known as a practical approach for nonlinear system modeling. In this approach, a selection of membership functions makes much effect upon the model performance. It is usually determined by the expert's knowledge for the objective systems. However, it is often difficult to give appropriate membership functions for unknown complex dynamical system without any prior information. In this paper, we deal with the approach to give appropriate fuzzy membership functions based on the observed input and output data using genetic algorithm. Then, an application to identification of nonlinear systems is considered and the availability of the proposed method is illustrated by some numerical examples.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"127 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":"114369592","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: 7
Evolving algorithms for constraint satisfaction 约束满足的进化算法
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1330866
S. Bain, J. Thornton, A. Sattar
{"title":"Evolving algorithms for constraint satisfaction","authors":"S. Bain, J. Thornton, A. Sattar","doi":"10.1109/CEC.2004.1330866","DOIUrl":"https://doi.org/10.1109/CEC.2004.1330866","url":null,"abstract":"This paper proposes a framework for automatically evolving constraint satisfaction algorithms using genetic programming. The aim is to overcome the difficulties associated with matching algorithms to specific constraint satisfaction problems. A representation is introduced that is suitable for genetic programming and that can handle both complete and local search heuristics. In addition, the representation is shown to have considerably more flexibility than existing alternatives, being able to discover entirely new heuristics and to exploit synergies between heuristics. In a preliminary empirical study, it is shown that the new framework is capable of evolving algorithms for solving the well-studied problem of Boolean satisfiability testing.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"37 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":"116284945","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: 10
Dynamic optimization of semantic annotation relevance 语义标注相关性的动态优化
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1331047
Dario Bonino, Fulvio Corno, Giovanni Squillero
{"title":"Dynamic optimization of semantic annotation relevance","authors":"Dario Bonino, Fulvio Corno, Giovanni Squillero","doi":"10.1109/CEC.2004.1331047","DOIUrl":"https://doi.org/10.1109/CEC.2004.1331047","url":null,"abstract":"The introduction of semantics in the next generation of the Web, the semantic Web, is strongly based on conceptual description of resources by means of semantic annotations. Effective technologies are therefore required lo correctly map the available syntactic information onto a set of relevant conceptual entities able to model the knowledge domain to which a resource belongs. In attempting to address such issue, we propose an evolutionary optimization of semantic annotation relevance which can improve text-to-concept mapping using information from both the syntactic and the semantic domains. The proposed algorithm leverages relevance information on resource contents, with respect to a subset of a given ontology, and performs several ontology navigation steps for extracting the set of most relevant annotations, in terms of semantic expressiveness. The fitness function of the algorithm is strongly time dependent since the set of annotation to be refined may vary according to user requests, to changes in the domain ontology and is related to the granularity of the annotation set.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"27 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":"128059138","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
Evolved gate arrays for image restoration 进化门阵列图像恢复
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1330996
A. Burian, J. Takala
{"title":"Evolved gate arrays for image restoration","authors":"A. Burian, J. Takala","doi":"10.1109/CEC.2004.1330996","DOIUrl":"https://doi.org/10.1109/CEC.2004.1330996","url":null,"abstract":"Evolved gate arrays with a proposed fitness function, are considered for image restoration. In this paper we proposed an on-chip solution for image restoration using an on-chip evolvable hardware method. The corrupted image is considered to be the environment of evolvable hardware structures, which are restoring the original through phenotypic evolution. We compare our solution with some classical techniques for image restoration.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"37 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":"125463284","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: 10
Hyper-heuristics applied to class and exam timetabling problems 超启发式应用于课堂和考试时间表问题
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1331099
P. Ross, J. Marín-Blázquez, E. Hart
{"title":"Hyper-heuristics applied to class and exam timetabling problems","authors":"P. Ross, J. Marín-Blázquez, E. Hart","doi":"10.1109/CEC.2004.1331099","DOIUrl":"https://doi.org/10.1109/CEC.2004.1331099","url":null,"abstract":"Combinatorial optimisation algorithms can be both slow and fragile. That is, the quality of results produced can vary considerably with the problem and with the parameters chosen and the user must hope or the best or search for problem-specific good parameters. The idea of hyper-heuristics is to search for a good, fast, deterministic algorithm built from easily-understood heuristics that shows good performance across a range of problems. In this paper we show how the idea can be applied to class and exam timetabling problems and report results on nontrivial problems. Unlike many optimisation algorithms, the generated algorithm does not involve and solution-improving search step, it is purely constructive.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"23 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":"132050287","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: 41
PASSSS: an implementation of a novel diversity strategy for handling constraints PASSSS:一种处理约束的新颖多样性策略的实现
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1330885
A. H. Aguirre, S. Rionda, C. C. Coello
{"title":"PASSSS: an implementation of a novel diversity strategy for handling constraints","authors":"A. H. Aguirre, S. Rionda, C. C. Coello","doi":"10.1109/CEC.2004.1330885","DOIUrl":"https://doi.org/10.1109/CEC.2004.1330885","url":null,"abstract":"In this paper, we introduce PASSSS (PAS/sup 4/), the Pareto archived and dominance selection with shrinkable search space evolutionary computation algorithm. The main contribution of this paper is a diversity control mechanism embedded into the selection operator of an evolutionary algorithm that can be used (with little or no modification) to solve both single-objective and multi-objective optimization problems. We present a detailed description of the PAS/sup 4/ algorithm, and illustrate its capabilities by solving several engineering design problems and some test functions from a well-known benchmark in evolutionary optimization. Additionally, PAS/sup 4/ is also used to solve continuous and discrete multiobjective engineering optimization problems.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"58 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":"130007599","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: 11
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