A variant of the SOM algorithm and its interpretation in the viewpoint of social influence and learning

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Title:	A variant of the SOM algorithm and its interpretation in the viewpoint of social influence and learning
Authors:	Su,MC;Zhao,YX
Contributors:	資訊工程研究所
Keywords:	MAP
Date:	2009
Issue Date:	2010-06-29 20:13:39 (UTC+8)
Publisher:	中央大學
Abstract:	The conventional self-organizing feature map (SOM) algorithm is usually interpreted as a computational model, which can capture main features of computational maps in the brain. In this paper, we present a variant of the SOM algorithm called the SOM-based optimization (SOMO) algorithm. The development of the SOMO algorithm was motivated by exploring the possibility of applying the SOM algorithm in continuous optimization problems. Through the self-organizing process, good solutions to an optimization problem can be simultaneously explored and exploited by the SOMO algorithm. In our opinion, the SOMO algorithm not only can be regarded as a biologically inspired computational model but also may be regarded as a new approach to a model of social influence and social learning. Several simulations are used to illustrate the effectiveness of the proposed optimization algorithm.
Relation:	NEURAL COMPUTING & APPLICATIONS
Appears in Collections:	[Graduate Institute of Computer Science and Information Engineering] journal & Dissertation

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