Evaluating Degree of Success in Power Plant Construction Project Based on Fuzzy Neural Network

Author

Huang, Yuansheng ; Liu, Qingchao ; Qiu, Zilong ; Wang, Mingyan

Author_Institution

Dept. of Econ. & Manage., North China Electr. Power Univ., Baoding

Volume

3

fYear

2008

fDate

18-20 Oct. 2008

Firstpage

206

Lastpage

210

Abstract

Using fuzzy neural network to evaluate the degree of success in power plant is this paper´s innovative points. First we give an index system, and then use the relative membership degree processing the date, which as the input sample of neural network. Then use PSO algorithm optimizes the BP neural network algorithm. Use this improved BP neural network to evaluate. It is more accuracy and speedily than BP neural network algorithm. Lastly, we can get a satisfaction result. This can be guiding the project construction.

Keywords

backpropagation; fuzzy neural nets; fuzzy set theory; power engineering computing; power plants; backpropagation neural networks; fuzzy neural network; particle swarm optimisation; power plant construction project; relative membership degree processing; Clustering algorithms; Conference management; Feedforward neural networks; Fuzzy neural networks; Fuzzy systems; Investments; Neural networks; Neurons; Power generation; Project management; PSO; evaluating degree of success; neural network; power plant construction project;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems and Knowledge Discovery, 2008. FSKD '08. Fifth International Conference on

Conference_Location

Shandong

Print_ISBN

978-0-7695-3305-6

Type

conf

DOI

10.1109/FSKD.2008.69

Filename

4666241