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A new evolutionary solution to the partitioning problem in local linear models (LLM) identification is developed. It consists in a master search process involving swarm intelligence (SI) based learning metaphor which trains the underlying system working space (SWS) oblique partitioning parameters, and a nested local optimization algorithm that estimates the LLM parameters in consequence. Finally two...
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