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- W2368090410 abstract "The quantum evolutionary algorithm(QEA) has received the widespread attention with its unique advantages such as fast convergence,short training time and global search capability. This paper mainly researches the quantum evolutionary algorithm by modeling with an adaptive network fuzzy inference system(ANFIS),this method uses the two advantages of both quantum evolutionary algorithm and ANFIS to optimize the population structure. It can optimize the global fuzzy inference system. Through simulation examples,the model of QEA-ANFIS is applied to the single-input single-output fuzzy system,the multiple-inputs single-output fuzzy system and multimodal nonlinear fuzzy system. This method can get the performance of the optimization of path tracking through the training data and testing data,and also get performance of the error comparison. The simulation results show that ANFIS has low accuracy,and the GA-ANFIS has a long training time QEA-ANFIS overcome these two flaws and can improve the precision and the training time." @default.
- W2368090410 created "2016-06-24" @default.
- W2368090410 creator A5053389245 @default.
- W2368090410 date "2014-01-01" @default.
- W2368090410 modified "2023-09-26" @default.
- W2368090410 title "Evolution ANFIS Model and Its Application Based on Quantum Evolutionary Algorithm" @default.
- W2368090410 hasPublicationYear "2014" @default.
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