Standard additive fuzzy system for stock price forecasting
ACIIDS'10 Proceedings of the Second international conference on Intelligent information and database systems: Part II
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This paper proposes an efficient approach that consists of an experimental design and a fuzzy-logic model (FLM) to generate macromodels for the simulation of microelectromechanical systems. Firstly, in the present approach, a force macromodel is adapted to perform the coupled simulations. Then, an experimental design is utilized to reduce the number of data needed for macromodel identification, and an FLM is chosen to fit the data. The identification scheme involves cluster estimation to determine the FLM structure and backpropagation method to efficiently obtain the FLM structure parameters that lead to an accurate macromodel. In order to verify the accuracy of the macromodel, the approach has been applied to a magnetic microactuator. The simulation results show that the force macromodel yielded errors of less than 1.5% for a 5-mum displacement. Furthermore, the dynamic coupled simulation takes only several minutes. The results demonstrate the efficiency and effectiveness of the current approach