A modified neural network based on subtractive clustering for bidding system
Min Han, Yingnan Fan, Wei Guo · 2006
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