• DocumentCode
    1563124
  • Title

    A modified neural network based on subtractive clustering for bidding system

  • Author

    Han, Min ; Fan, Yingnan ; Guo, Wei

  • Author_Institution
    Sch. of Electron. & Inf. Engg., Dalian Univ. of Technol.
  • Volume
    1
  • fYear
    2005
  • Firstpage
    128
  • Lastpage
    133
  • Abstract
    The paper presents a modified neural network based on subtractive clustering (NN-SC). It can be used to estimate the mark-up of construction bidding system. In recent years, many neural fuzzy approaches to model are proposed. But they are limited for complex and arbitrary in computation and structure. In this paper, the NN-SC is proposed to overcome the drawbacks mentioned above and have fuzzy inference and self-learning ability. It uses subtractive clustering to generate rules and form rulebase. With rule inference steps, it is convenient to determine the degree of applicability for each rule. Therefore, it has high degree of transparency, compact structure and computational efficiency. And based on neural network, nonlinear mapping between input and output is accomplished. With the simulation, it is proven that the proposed network is and has good performance
  • Keywords
    construction; fuzzy logic; fuzzy neural nets; fuzzy reasoning; fuzzy set theory; construction bidding system; fuzzy inference; neural fuzzy model; neural network; nonlinear mapping; rule inference steps; self-learning ability; subtractive clustering; Clustering algorithms; Computer networks; Fuzzy logic; Fuzzy neural networks; Fuzzy reasoning; Fuzzy sets; Fuzzy systems; Neural networks; Paper technology; Partitioning algorithms; biding system; neural network; rule; subtractive clustering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks and Brain, 2005. ICNN&B '05. International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    0-7803-9422-4
  • Type

    conf

  • DOI
    10.1109/ICNNB.2005.1614582
  • Filename
    1614582