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
Link To Document :
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