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NHFCNNC: A New Fuzzy Neural Network Algorithm Based on Matrix and Its Application

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Artificial Intelligence and Computational Intelligence (AICI 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7530))

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Abstract

A new fuzzy neural network algorithm (NHFCNNC) based on matrix is presented, which is applied to the text clustering. The main defect of traditional methods of fuzzy neural network is to know the number of clustering in advance. A new cohesion formula is put forward in NHFCNNC algorithm. The lines (or columns) of the membership matrix of NHFCNNC algorithm are sorted and transformed; the membership matrix is blocked to realize hierarchical clustering. The experiment shows the precision and the efficiency of clustering NHFCNNC are higher than traditional fuzzy neural network.

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Author information

Authors and Affiliations

  1. Institute of Systems Engineering, Dalian University of Technology, Dalian, Liaoning, 116024, China

    Zhiyong Liu & Guishi Deng

  2. Department of Mathematics, Anshan Normal University, Anshan, Liaoning, 114005, China

    Zhiyong Liu & Xinqing Geng

Authors
  1. Zhiyong Liu
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  2. Xinqing Geng
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  3. Guishi Deng
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Editor information

Editors and Affiliations

  1. School of Computer and Information Engineering, Shanghai University of Electric Power, 200090, Shanghai, China

    Jingsheng Lei

  2. Deaprtment of Business Administration, Caritas Institute of Higher Education, 18 Chui Ling Road, Tseung Kwan O, Hong Kong, China

    Fu Lee Wang

  3. School of Business Information Technology and Logistics, RMIT University, City Campus, 124 la Tobre Street, 3000, Melbourne, Victoria, Australia

    Hepu Deng

  4. School of Electronics and Information, Tongji University, 201804, Shanghai, China

    Duoqian Miao

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© 2012 Springer-Verlag Berlin Heidelberg

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Liu, Z., Geng, X., Deng, G. (2012). NHFCNNC: A New Fuzzy Neural Network Algorithm Based on Matrix and Its Application. In: Lei, J., Wang, F.L., Deng, H., Miao, D. (eds) Artificial Intelligence and Computational Intelligence. AICI 2012. Lecture Notes in Computer Science(), vol 7530. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33478-8_22

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  • DOI: https://doi.org/10.1007/978-3-642-33478-8_22

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33477-1

  • Online ISBN: 978-3-642-33478-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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