A self-organizing neuro-fuzzy network based on first order effect sensitivity analysis

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	A self-organizing neuro-fuzzy network based on first order effect sensitivity analysis
	Chen, Cheng 1; Wang, Fei-Yue1,2
发表期刊	NEUROCOMPUTING
	2013-10-22
卷号	118 期号:0 页码:21-32
文章类型	Article
摘要	As an effective method that can provide the information about the influence of inputs on the variation of output, variance based sensitivity analysis is widely used to determine the structure of neural networks. In the past, the global sensitivity analysis method for the total effect has been used for the structure learning of neural networks and various growing and pruning algorithms have been developed. In this paper, we find that neuro-fuzzy networks have the characteristics of additive models in which the first order effect index of the influence can provide the same comprehensive information as the total effect index, thus we only need to analyze the first order effects of the inputs to their output layers. Based on this observation, many low-cost effective methods for the first order effect global sensitivity can be used in for developing self-organizing neuro-fuzzy networks. Specifically, Random Balance Designs is employed here for sensitivity analysis. In addition, we also introduce the concept of systemic fluctuation of neuro-fuzzy networks to determine whether adjustment is needed for a network. This concept helps us to build a new procedure about the leaning of self-organizing neuro-fuzzy networks and to accelerate its speed of convergence in learning and organizing. Examples of simulations have demonstrated that our proposed method performs better than other existing procedures for self-organizing neuro-fuzzy networks, especially in learning of the network structure. (C) 2013 Elsevier B.V. All rights reserved.
关键词	Neuro-fuzzy Networks First Order Effect Sensitivity Analysis Systemic Fluctuation
WOS标题词	Science & Technology ; Technology
关键词[WOS]	SEQUENTIAL LEARNING ALGORITHM ; FUNCTION APPROXIMATION ; PRUNING ALGORITHM ; SYSTEM ; OUTPUT
收录类别	SCI
语种	英语
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000323693700003
引用统计	被引频次：11[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/3672
专题	多模态人工智能系统全国重点实验室_平行智能技术与系统团队
通讯作者	Chen, Cheng
作者单位	1.Chinese Acad Sci, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Natl Univ Def Technol, Ctr Mil Computat Expt & Parallel Syst, Changsha 410073, Hunan, Peoples R China
第一作者单位	中国科学院自动化研究所
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Chen, Cheng,Wang, Fei-Yue. A self-organizing neuro-fuzzy network based on first order effect sensitivity analysis[J]. NEUROCOMPUTING,2013,118(0):21-32.
APA	Chen, Cheng,&Wang, Fei-Yue.(2013).A self-organizing neuro-fuzzy network based on first order effect sensitivity analysis.NEUROCOMPUTING,118(0),21-32.
MLA	Chen, Cheng,et al."A self-organizing neuro-fuzzy network based on first order effect sensitivity analysis".NEUROCOMPUTING 118.0(2013):21-32.

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