| 一种新的模糊神经元网络建模方法 |
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| 引用本文： | 张平安,王慧琴,李人厚.一种新的模糊神经元网络建模方法[J].西安建筑科技大学学报(自然科学版),2000,32(2):183-187. |
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| 作者姓名： | 张平安 王慧琴 李人厚 |
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| 作者单位： | 1. 西安交通大学系统工程研究所,陕西,西安,710049
2. 西安建筑科技大学信控学院,陕西,西安,710055 |
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| 基金项目： | 西安交通大学科研基金资助 |
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| 摘 要： | 基于零阶Ｔ－Ｓ模糊模型，本文指出了一种实用的输入输出的数据进行复杂系统的模糊神经元网络建模的方法，该方法的主要目的是解决模糊神经元网络中结构辨识的困难。 种所谡语言模型被用来寻找系统输入变量的最佳组合。
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| 关 键 词： | 模糊神经元网络 模糊聚类 系统辨识 |
| 文章编号： | 1006-7930(2000)02-0183-05 |
| 修稿时间： | 2000-02-22 |
A new approach to fuzzy-neural-network modeling |
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| ZHANG Ping-an,WANG Hui-qin,LI Ren-hou.A new approach to fuzzy-neural-network modeling[J].Journal of Xi'an University of Architecture & Technology,2000,32(2):183-187. |
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| Authors: | ZHANG Ping-an WANG Hui-qin LI Ren-hou |
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| Affiliation: | ZHANG Pin-an
;(Institute of Systems Engineering, Xi'an Jiaotong University, Xi'an 710049, China);WANG Hui-qin
;(School of Information and Control, Xi'an Univ. Of Arch. Tech., Xi'an 710055, China);LI Ren-hou
;(Institute of Systems Engineering, Xi'an Jiaotong University, Xi'an 710049, China) |
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| Abstract: | Based on zero-order takagi-sugeno model, a simple yet effective approach to fuzzy-neural-network (FNN) modeling for complex systems with input-outpnt data is presented. The main purpose of the present method is to solve the difficulty of structure identification in FNN. A so-called linguistic model is used to find the optimal combination of system input variables. Then, in the stage of input variable selection, we neither estimate the parameters of the fuzzy model nor determine the nuraher of the fuzzy rules. Since an FCM-based self-adaptive fuzzy clustering technique is employed to determine the proper structure of the FNN and set the initial weights in advance,the network can be trained rapidly. Furthermore,a modified membership function is also provided to improve the identification accuracy of the FNN. Effectiveness of the present method is verified by a simulation for a practical modeling. |
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| Keywords: | fuzzy-neural-network fuzzy clustering system identification |
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