Load identification of algorithm based on dynamic fuzzy granular neural networkChinese Full Text

TAO Yong-qin1,2,CUI Du-wu1(1.School of Computer Science and Engineering,Xi’an University of Technology,Xi’an 710048,China;2.Department of Computer Science and Technology,Xi’an Jiaotong University,Xi’an 710049,China.)

Abstract: An algorithm based on dynamic fuzzy granular neural network is proposed for the characteristics of power load,which is time-variant,variable structure and non-linear.The quotient space theory of granular computing and fuzzy neural network technology are used in power load modeling.Elliptic basis function and fuzzy ζ-completeness are also used as a distribution mechanism of on-line parameter to avoid the randomicity of the initialization options.Online self-adapting adjustment is executed on the width of input variable according to fuzzy rules and the importance of input variables,and then the load parameters and the structure can be identified synchronously.Experimental results show the feasibility and effectiveness of this method.

Keywords：

load model; parameter identification; constructure identification; granular computing; dynamic fuzzy neural network;

DOI：
10.13195/j.cd.2011.04.42.taoyq.002
Series：
Subject：
Classification Code：
TM714

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Load identification of algorithm based on dynamic fuzzy granular neural networkChinese Full Text

TAO Yong-qin1,2,CUI Du-wu1(1.School of Computer Science and Engineering,Xi’an University of Technology,Xi’an 710048,China;2.Department of Computer Science and Technology,Xi’an Jiaotong University,Xi’an 710049,China.)

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