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Because of globalization, fast changes of technology and short life cycle of products, enhancing the accuracy of demand forecasts becomes one of the important issues for managers. The objective of this paper is to analyze and explore given data of orders using adaptive neuro-fuzzy inference system (ANFIS) and to draw up, by ANFIS learning mechanism, the relational rules from historical order data,...
This paper presented a new prediction model for material property (strength of materials for gray cast iron) based on composition and microstructure using a recent learning algorithm called Sensitivity Based Linear learning Method (SBLLM). This method was proposed in order to address the problems of back propagation learning algorithm for feed forward neural network. Thus we have made use of this...
A new training algorithm for hierachical hybrid fuzzy - neural network (HHFNN) based on Takagi - Sugeno (T-S) fuzzy system is proposed in this paper. Triangular membership function is adopted. And to reduce the strong interaction among discrete input variables, coefficient contraction method is employed; ridge regression function is used in the THEN parts of fuzzy rules. At last, pyrimidines medical...
The self-adaptation and self-studying features of neural networks have been combined with the logical reasoning ability of fuzzy system to produce a fuzzy system based neural networks, BP arithmetic is used to adjust system parameters. Finally the fuzzy neural networks model with the wind farms calculation is established, as compared with the model of multi-variant linear regression, the fuzzy neural...
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