Structure Optimization of Locally Linear Model Tree Using Extermal Optimization

Khalil Sharifi, Mohammad Reza Ahmadzadeh
2011 Journal of Intelligent Procedures in Electrical Technology  
Locally Linear Model Tree (LOLIMOT) algorithm proposed by Nelles deals with local linear nearo-fuzzy models that is based on divides-and-conquer strategy that a complex modeling problem is divided to a number of smaller and thus simpler sub problems. So the characteristic of such a neuro-fuzzy model depends on division strategy for the original complex problem. For finding the best output the algorithm divides the problem to a number of local linear models (LLMs) , then continues with finding
more » ... nues with finding the worst LLM and dividing it. LOLIMOT splits the local linear models into two equal halves with an axis-orthogonal decomposition strategy. In this paper a new approach based on extremeal optimization (EO) is used to optimize the structure of LOLIMOT. Simulation results show the effectiveness of the enhanced LOLIMOT to have a higher precision with optimal number of neurons.
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