Polynomial Neural Network Classifiers Based on Data Preprocessing and Space Search Optimization

Wei Huang, Sung Kwun Oh, Witold Pedrycz

科研成果: 书/报告/会议事项章节会议稿件同行评审

1 引用 (Scopus)

摘要

In this paper, we propose a novel architecture of polynomial neural network classifier (PNNC) with the aid of data preprocessing technique and space search optimization, which adopts accelerated convergence mechanism instead of purely random search. Two type of polynomials are adopted for constructing discriminate functions in the PNNC to alleviate the limitation of relatively simple geometry using linear discriminate function in the conventional neural network classifiers. Space search optimization is exploited here to realize structure optimizes and parameter optimize in the design of PNNC. Moreover, data preprocessing techniques are used to reduce the dimension of training data. The proposed PNNC is compared with some well-known classifiers based on several benchmark data sets. Experimental results illustrate the effectiveness of PNNCs.

源语言英语
主期刊名Proceedings - 2016 Joint 8th International Conference on Soft Computing and Intelligent Systems and 2016 17th International Symposium on Advanced Intelligent Systems, SCIS-ISIS 2016
出版商Institute of Electrical and Electronics Engineers Inc.
769-773
页数5
ISBN(电子版)9781467390415
DOI
出版状态已出版 - 28 12月 2016
已对外发布
活动8th Joint International Conference on Soft Computing and Intelligent Systems and 17th International Symposium on Advanced Intelligent Systems, SCIS-ISIS 2016 - Sapporo, Hokkaido, 日本
期限: 25 8月 201628 8月 2016

出版系列

姓名Proceedings - 2016 Joint 8th International Conference on Soft Computing and Intelligent Systems and 2016 17th International Symposium on Advanced Intelligent Systems, SCIS-ISIS 2016

会议

会议8th Joint International Conference on Soft Computing and Intelligent Systems and 17th International Symposium on Advanced Intelligent Systems, SCIS-ISIS 2016
国家/地区日本
Sapporo, Hokkaido
时期25/08/1628/08/16

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