Simulated Annealing for Automated Definition of Fuzzy Sets in Human Central Nervous System Modeling
The main goal of this research is to study the usefulness of the Simulated Annealing (SA) approach, developed in the context of the Fuzzy Inductive Reasoning (FIR) methodology, for the automatic identification of fuzzy partitions in the human Central Nervous System (CNS) modeling problem. The SA algorithm can be viewed as a pre-process of the FIR methodology that allows the modeler to use it in a more efficient way. Two different SA algorithm cost functions have been studied and evaluated in this paper. The new approach is applied to obtain accurate models for the five controllers that compose the CNS. The results are compared and discussed with those obtained by other inductive methodologies for the same problem.
KeywordsCost Function Mean Square Error Simulated Annealing Simulated Annealing Algorithm Fuzzy Partition
- 2.Nebot, A.: Automatic tuning of fuzzy paryitions in inductive reasoning. In: Sanfeliu, A., Ruiz-Shulcloper, J. (eds.) CIARP 2003. LNCS, vol. 2905, p. 8. Springer, Heidelberg (2003)Google Scholar