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IEEE Transactions on Evolutionary Computation

Issue 4 • Date Aug. 2007

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Displaying Results 1 - 15 of 15
  • Table of contents

    Publication Year: 2007, Page(s): C1
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  • IEEE Transactions on Evolutionary Computation publication information

    Publication Year: 2007, Page(s): C2
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  • Time Series Forecasting for Dynamic Environments: The DyFor Genetic Program Model

    Publication Year: 2007, Page(s):433 - 452
    Cited by:  Papers (28)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (685 KB) | HTML iconHTML

    Several studies have applied genetic programming (GP) to the task of forecasting with favorable results. However, these studies, like those applying other techniques, have assumed a static environment, making them unsuitable for many real-world time series which are generated by varying processes. This study investigates the development of a new ldquodynamicrdquo GP model that is specifically tail... View full abstract»

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  • Where Are the Niches? Dynamic Fitness Sharing

    Publication Year: 2007, Page(s):453 - 465
    Cited by:  Papers (29)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1019 KB) | HTML iconHTML

    The problem of locating all the optima within a multimodal fitness landscape has been widely addressed in evolutionary computation, and many solutions, based on a large variety of different techniques, have been proposed in the literature. Among them, fitness sharing (FS) is probably the best known and the most widely used. The main criticisms to FS concern both the lack of an explicit mechanism f... View full abstract»

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  • Natural Encoding for Evolutionary Supervised Learning

    Publication Year: 2007, Page(s):466 - 479
    Cited by:  Papers (14)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (854 KB) | HTML iconHTML

    Some of the most influential factors in the quality of the solutions found by an evolutionary algorithm (EA) are a correct coding of the search space and an appropriate evaluation function of the potential solutions. EAs are often used to learn decision rules from datasets, which are encoded as individuals in the genetic population. In this paper, the coding of the search space for the obtaining o... View full abstract»

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  • Evolutionary Gradient Search Revisited

    Publication Year: 2007, Page(s):480 - 495
    Cited by:  Papers (6)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (659 KB) | HTML iconHTML

    Evolutionary gradient search (EGS) is an approach to optimization that combines features of gradient strategies with ideas from evolutionary computation. Recently, several modifications to the algorithm have been proposed with the goal of improving its robustness in the presence of noise and its suitability for implementation on parallel computers. In this paper, the value of the proposed modifica... View full abstract»

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  • Learning Classifier System Ensembles With Rule-Sharing

    Publication Year: 2007, Page(s):496 - 502
    Cited by:  Papers (18)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1245 KB) | HTML iconHTML

    This paper presents an investigation into exploiting the population-based nature of learning classifier systems (LCSs) for their use within highly parallel systems. In particular, the use of simple payoff and accuracy-based LCSs within the ensemble machine approach is examined. Results indicate that inclusion of a rule migration mechanism inspired by parallel genetic algorithms is an effective way... View full abstract»

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  • Applying Genetic Parallel Programming to Synthesize Combinational Logic Circuits

    Publication Year: 2007, Page(s):503 - 520
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (966 KB) | HTML iconHTML

    Experimental results show that parallel programs can be evolved more easily than sequential programs in genetic parallel programming (GPP). GPP is a novel genetic programming paradigm which evolves parallel program solutions. With the rapid development of lookup-table-based (LUT-based) field programmable gate arrays (FPGAs), traditional circuit design and optimization techniques cannot fully explo... View full abstract»

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  • Revisiting the Foundations of Artificial Immune Systems for Data Mining

    Publication Year: 2007, Page(s):521 - 540
    Cited by:  Papers (44)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (849 KB) | HTML iconHTML

    This paper advocates a problem-oriented approach for the design of artificial immune systems (AIS) for data mining. By problem-oriented approach we mean that, in real-world data mining applications the design of an AIS should take into account the characteristics of the data to be mined together with the application domain: the components of the AIS - such as its representation, affinity function,... View full abstract»

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  • Coarse-Grained Dynamics for Generalized Recombination

    Publication Year: 2007, Page(s):541 - 557
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (615 KB) | HTML iconHTML

    An exact microscopic model for the dynamics of a genetic algorithm with generalized recombination is presented. Generalized recombination is a new model for the exchange of genetic material from parents to offspring that generalizes and subsumes standard operators, such as homologous crossover, inversion and duplication, and in which a particular gene in the offspring may originate from any parent... View full abstract»

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  • IEEE Congress on Evolutionary Computation

    Publication Year: 2007, Page(s): 558
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  • 2008 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology

    Publication Year: 2007, Page(s): 559
    Request permission for commercial reuse | PDF file iconPDF (584 KB)
    Freely Available from IEEE
  • Special issue on swarm intelligence

    Publication Year: 2007, Page(s): 560
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    Freely Available from IEEE
  • IEEE Computational Intelligence Society Information

    Publication Year: 2007, Page(s): C3
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  • IEEE Transactions on Evolutionary Computation Information for authors

    Publication Year: 2007, Page(s): C4
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Aims & Scope

IEEE Transactions on Evolutionary Computation publishes archival quality original papers in evolutionary computation and related areas including nature-inspired algorithms, population-based methods, and optimization where selection and variation are integral, and hybrid systems where these paradigms are combined. Purely theoretical papers are considered as are application papers that provide general insights into these areas of computation.
 

Full Aims & Scope

Meet Our Editors

Editor-in-Chief

Dr. Kay Chen Tan (IEEE Fellow)

Department of Electrical and Computer Engineering

National University of Singapore

Singapore 117583

Email: eletankc@nus.edu.sg

Website: http://vlab.ee.nus.edu.sg/~kctan