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Titlebook: Advances in Swarm Intelligence; First International Ying Tan,Yuhui Shi,Kay Chen Tan Conference proceedings 2010 Springer-Verlag Berlin Hei

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Fuzzy Cluster Centers Separation Clustering Using Possibilistic Approachx trace that controls the distances between the class centroids. Based on the principle of cluster centers separation, fuzzy cluster centers separation (FCCS) clustering is an extended fuzzy c-means (FCM) clustering algorithm. FCCS attaches importance to both the fuzzy within cluster scatter matrix
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A Class of Fuzzy Portfolio Optimization Problems: E-S Models(E-S) model for portfolio optimization problem. Since the spread is defined by Lebesgue-Stieltjes (L-S) integral, its computation for general fuzzy variables is a challenge issue for research, and usually depends on approximation scheme and soft computing. But for frequently used trapezoidal and tri
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Application of PSO-Adaptive Neural-fuzzy Inference System (ANFIS) in Analog Circuit Fault Diagnosis proposed. Using subtractive clustering and Particle Swarm Optimization (PSO)-hybrid algorithm as a tool for building the fault diagnosis model, then, the model of fault diagnosis system was used to the circuit fault diagnosis. Simulation results have shown that the method is more effective.
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Cooperation Partners Selection for Multiple-Core-Type MPNsis of multiple-core-type modular producing network cooperation partner selection, this paper suggests that Comprehensive Evaluation Method to choose partners is to choose the multiple-core-type modular producing network cooperation partners in accordance with the principles of the lowest total cost
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Computational Intelligence Algorithms Analysis for Smart Grid Cyber Securityk. The North American Electric Reliability Corporation (NERC) has thus developed several iterations of cyber security standards. According to the NERC cyber standards CIP-002-2 requirements, in this paper, we present cyber security risk analysis using computational intelligence methods and review on
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Using AOBP for Definitional Question Answeringssible which include 3 categories. The first is based on language model. We train our language model on four different corpora. The second resource is the syntax dependency relations, which are extracted by Minipar. And the third resource contains only one feature, the document score provided by Inf
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