IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews)

Issue 2 • May 2005

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  • Table of contents

    Publication Year: 2005, Page(s): c1
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  • IEEE Transactions on Systems, Man, and Cybernetics—Part C: Applications and Reviews publication information

    Publication Year: 2005, Page(s): c2
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  • Guest Editorial Special Issue on Knowledge Extraction and Incorporation in Evolutionary Computation

    Publication Year: 2005, Page(s):129 - 130
    Cited by:  Papers (2)
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  • A distributed evolutionary classifier for knowledge discovery in data mining

    Publication Year: 2005, Page(s):131 - 142
    Cited by:  Papers (11)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1016 KB) | HTML iconHTML

    This paper presents a distributed coevolutionary classifier (DCC) for extracting comprehensible rules in data mining. It allows different species to be evolved cooperatively and simultaneously, while the computational workload is shared among multiple computers over the Internet. Through the intercommunications among different species of rules and rule sets in a distributed manner, the concurrent ... View full abstract»

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  • Agent-based evolutionary approach for interpretable rule-based knowledge extraction

    Publication Year: 2005, Page(s):143 - 155
    Cited by:  Papers (43)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1072 KB) | HTML iconHTML

    An agent-based evolutionary approach is proposed to extract interpretable rule-based knowledge. In the multiagent system, each fuzzy set agent autonomously determines its own fuzzy sets information, such as the number and distribution of the fuzzy sets. It can further consider the interpretability of fuzzy systems with the aid of hierarchical chromosome formulation and interpretability-based regul... View full abstract»

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  • Evolutionary feature synthesis for object recognition

    Publication Year: 2005, Page(s):156 - 171
    Cited by:  Papers (35)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1728 KB) | HTML iconHTML

    Features represent the characteristics of objects and selecting or synthesizing effective composite features are the key to the performance of object recognition. In this paper, we propose a coevolutionary genetic programming (CGP) approach to learn composite features for object recognition. The knowledge about the problem domain is incorporated in primitive features that are used in the synthesis... View full abstract»

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  • Knowledge interaction with genetic programming in mechatronic systems design using bond graphs

    Publication Year: 2005, Page(s):172 - 182
    Cited by:  Papers (21)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (569 KB) | HTML iconHTML

    This paper describes a unified network synthesis approach for the conceptual stage of mechatronic systems design using bond graphs. It facilitates knowledge interaction with evolutionary computation significantly by encoding the structure of a bond graph in a genetic programming tree representation. On the one hand, since bond graphs provide a succinct set of basic design primitives for mechatroni... View full abstract»

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  • Accelerating evolutionary algorithms with Gaussian process fitness function models

    Publication Year: 2005, Page(s):183 - 194
    Cited by:  Papers (96)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (574 KB) | HTML iconHTML

    We present an overview of evolutionary algorithms that use empirical models of the fitness function to accelerate convergence, distinguishing between evolution control and the surrogate approach. We describe the Gaussian process model and propose using it as an inexpensive fitness function surrogate. Implementation issues such as efficient and numerically stable computation, exploration versus exp... View full abstract»

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  • Clustering and learning Gaussian distribution for continuous optimization

    Publication Year: 2005, Page(s):195 - 204
    Cited by:  Papers (49)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (685 KB) | HTML iconHTML

    Since the Estimation of Distribution Algorithm (EDA) was introduced, different approaches in continuous domains have been developed. Initially, the single Gaussian distribution was broadly used when building the probabilistic models, which would normally mislead the search when dealing with multimodal functions. Some researchers later constructed EDAs that take advantage of mixture probability dis... View full abstract»

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  • A constraint-based genetic algorithm approach for mining classification rules

    Publication Year: 2005, Page(s):205 - 220
    Cited by:  Papers (7)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2528 KB) | HTML iconHTML

    Data mining is an information extraction process that aims to discover valuable knowledge in databases. Existing genetic algorithms (GAs) designed for rule induction evaluates the rules as a whole via a fitness function. Major drawbacks of GAs for rule induction include computation inefficiency, accuracy and rule expressiveness. In this paper, we propose a constraint-based genetic algorithm (CBGA)... View full abstract»

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  • An evolutionary algorithm for solving nonlinear bilevel programming based on a new constraint-handling scheme

    Publication Year: 2005, Page(s):221 - 232
    Cited by:  Papers (86)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (636 KB) | HTML iconHTML

    In this paper, a special nonlinear bilevel programming problem (nonlinear BLPP) is transformed into an equivalent single objective nonlinear programming problem. To solve the equivalent problem effectively, we first construct a specific optimization problem with two objectives. By solving the specific problem, we can decrease the leader's objective value, identify the quality of any feasible solut... View full abstract»

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  • Search biases in constrained evolutionary optimization

    Publication Year: 2005, Page(s):233 - 243
    Cited by:  Papers (164)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (758 KB) | HTML iconHTML

    A common approach to constraint handling in evolutionary optimization is to apply a penalty function to bias the search toward a feasible solution. It has been proposed that the subjective setting of various penalty parameters can be avoided using a multiobjective formulation. This paper analyzes and explains in depth why and when the multiobjective approach to constraint handling is expected to w... View full abstract»

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  • Evolutionary fuzzy neural networks for hybrid financial prediction

    Publication Year: 2005, Page(s):244 - 249
    Cited by:  Papers (22)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (381 KB) | HTML iconHTML

    In this paper, an evolutionary fuzzy neural network using fuzzy logic, neural networks (NNs), and genetic algorithms (GAs) is proposed for financial prediction with hybrid input data sets from different financial domains. A new hybrid iterative evolutionary learning algorithm initializes all parameters and weights in the five-layer fuzzy NN, then uses GA to optimize these parameters, and finally a... View full abstract»

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  • Genetic recurrent fuzzy system by coevolutionary computation with divide-and-conquer technique

    Publication Year: 2005, Page(s):249 - 254
    Cited by:  Papers (5)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (343 KB) | HTML iconHTML

    A genetic recurrent fuzzy system which automates the design of recurrent fuzzy networks by a coevolutionary genetic algorithm with divide-and-conquer technique (CGA-DC) is proposed in this paper. To solve temporal problems, the recurrent fuzzy network constructed from a series of recurrent fuzzy if-then rules is adopted. In the CGA-DC, based on the structure of a recurrent fuzzy network, the desig... View full abstract»

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  • Knowledge-based fast evaluation for evolutionary learning

    Publication Year: 2005, Page(s):254 - 261
    Cited by:  Papers (9)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (478 KB) | HTML iconHTML

    The increasing amount of information available is encouraging the search for efficient techniques to improve the data mining methods, especially those which consume great computational resources, such as evolutionary computation. Efficacy and efficiency are two critical aspects for knowledge-based techniques. The incorporation of knowledge into evolutionary algorithms (EAs) should provide either b... View full abstract»

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  • Multiobjective GA optimization using reduced models

    Publication Year: 2005, Page(s):261 - 265
    Cited by:  Papers (25)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (196 KB) | HTML iconHTML

    In this paper, we propose a novel method for solving multiobjective optimization problems using reduced models. Our method, called objective exchange genetic algorithm for design optimization (OEGADO), is intended for solving real-world application problems. For such problems, the number of objective evaluations performed is a critical factor as a single objective evaluation can be quite expensive... View full abstract»

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  • A comparative study of three evolutionary algorithms incorporating different amounts of domain knowledge for node covering problem

    Publication Year: 2005, Page(s):266 - 271
    Cited by:  Papers (17)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (212 KB) | HTML iconHTML

    This paper compares three different evolutionary algorithms for solving the node covering problem: EA-I relies on the definition of the problem only without using any domain knowledge, while EA-II and EA-III employ extra heuristic knowledge. In theory, it is proven that all three algorithms can find an optimal solution in finite generations and find a feasible solution efficiently; but none of the... View full abstract»

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  • Special issue on interdependencies in civil infrastructure systems

    Publication Year: 2005, Page(s): 272
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  • IEEE Systems, Man, and Cybernetics Society Information

    Publication Year: 2005, Page(s): c3
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  • IEEE Transactions on Systems, Man, and Cybernetics—Part C: Applications and Reviews Information for authors

    Publication Year: 2005, Page(s): c4
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Aims & Scope

This Transactions ceased production in 2012. The current retitled publication is IEEE Transactions on Human-Machine Systems.
http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6221037

Overview, tutorial and application papers concerning all areas of interest to the SMC Society: systems engineering, human factors and human machine systems, and cybernetics and computational intelligence. 

Authors should submit human-machine systems papers to the IEEE Transactions on Human-Machine Systems.

Authors should submit systems engineering papers to the IEEE Transactions on Systems, Man and Cybernetics: Systems.

Authors should submit cybernetics papers to the IEEE Transactions on Cybernetics.

Authors should submit social system papers to the IEEE Transactions on Computational Social Systems.

 

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Dr. Vladimir Marik
(until 31 December 2012)