By István Borgulya (auth.), Professor Dr. Bernd Reusch (eds.)
This e-book constitutes the refereed lawsuits of the eighth Dortmund Fuzzy Days, held in Dortmund, Germany, 2004. The Fuzzy-Days convention has tested itself as a global discussion board for the dialogue of recent leads to the sphere of Computational Intelligence. all of the papers needed to suffer an intensive overview ensuring a fantastic caliber of the programme. The papers are dedicated to foundational and sensible concerns in fuzzy structures, neural networks, evolutionary algorithms, and computing device studying and hence hide the complete variety of computational intelligence.
Read or Download Computational Intelligence, Theory and Applications: International Conference 8th Fuzzy Days in Dortmund, Germany, Sept. 29–Oct. 01, 2004 Proceedings PDF
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Additional info for Computational Intelligence, Theory and Applications: International Conference 8th Fuzzy Days in Dortmund, Germany, Sept. 29–Oct. 01, 2004 Proceedings
Sample text
This appealing scheme has revealed itself as a competitive approach for optimization, owing to its simplicity and relatively low computational cost. Several extensions have been proposed in order to further improve its performance. F. Romero and C. F. Romero and C. Cotta search or other EC mechanisms [6, 7]. In this work, we propose the use of multiple cooperative swarms, each of which tries to solve the original problem in partial isolation following the philosophy of island-model evolutionary algorithms [8].
2 Known Approaches Like in many areas of the theory of fuzzy sets, also in the present one a quite active research is to be noted. We would like to mention three directions– those we know about. It is (i) the logical approach; (ii) the usage of fuzzy relations; (iii) interpolation based on linearity notions. Let a fuzzy if-then rule base (u1 , v1 ), . . , (uk , vk ) of pairs from F(Ξ) × F(Υ ) for domains Ξ and Υ be given, and let us in this section adopt the usual notion of a fuzzy set as a function from a base set to [0,1].
Notice the use of a log-scale in the Y-axis. 5 5 x 105 Fig. 4. Evolution of fitness (averaged for 30 runs) for different number of swarms in the Rosenbrock function. The left graph corresponds to the RING topology, and the right one to the COMPLETE topology. Notice the use of a log-scale in the Y-axis. at a faster pace than synchronization by diffusion does. The latter is a more exploratory strategy, due to the lower coupling of swarms. The behavior in the Sphere function is essentially the same as described before for the Rastrigin function (cf.