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Titlebook: Advances in Swarm Intelligence, Part II; Second International Ying Tan,Yuhui Shi,Guoyin Wang Conference proceedings 2011 Springer-Verlag Gm

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發(fā)表于 2025-3-25 06:47:43 | 只看該作者
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發(fā)表于 2025-3-25 07:40:41 | 只看該作者
Impulsive Consensus in Networks of Multi-agent Systems with Any Communication Delaysd dynamical systems, a simple impulsive consensus protocol for such networks is proposed, and a generic criterion for solving the average consensus problem is analytically derived. Compared with some existing works, a distinctive feature of this work is to address average consensus problem for netwo
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發(fā)表于 2025-3-25 14:57:14 | 只看該作者
FDClust: A New Bio-Inspired Divisive Clustering Algorithminspired divisive clustering algorithm FDClust (Artificial Fish based Divisive Clustering algorithm). FDClust takes inspiration from the social organization and the encounters of fish shoals. In this algorithm, each artificial fish (agents) is identified with one object to be clustered. Agents move
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發(fā)表于 2025-3-25 17:02:11 | 只看該作者
Mining Class Association Rules from Dynamic Class Coupling Data to Measure Class Reusability Patternention to the measurement of reusability. There is a tremendous scope of using various data mining techniques in identifying set of software components having more dependency amongst each other, making each of them less reusable in isolation. For object-oriented development paradigm, class coupling
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發(fā)表于 2025-3-25 23:30:24 | 只看該作者
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發(fā)表于 2025-3-26 03:27:50 | 只看該作者
Advances in Swarm Intelligence, Part II978-3-642-21524-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
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發(fā)表于 2025-3-26 06:36:50 | 只看該作者
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發(fā)表于 2025-3-26 17:59:14 | 只看該作者
The Properties of Birandom Multiobjective Programming Problems (BRMOP) problem and its expected value model. Then we present the concepts of non-inferior solution, called expected-value efficient solutions and expected-value wake efficient solutions, and their properties are also discussed. The results obtained in this paper can provide theoretical basis for designing algorithms to solve the BRMOP problem.
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