Title :
Competition Competence Evaluation of Power Generating Enterprises using Improved Neural Network
Author :
Sun, Wei ; Shang, Wei ; Qi, Jian-Xun
Author_Institution :
Sch. of Bus. & Adm., North China Electr. Power Univ., Baoding
Abstract :
With the development of electricity market reformation in China, it is especially important to evaluate the competition competence of power generating enterprises. Based on the characteristics of their, this paper bring forwards an index system to evaluate the competition competence of power generating enterprises. Improved BP neural network is introduced which is aimed at feedback lag and easily falling into the local optimal minimum. From dynamic controlling quotients, the methods at input layer and out layer errs is improved. The computation time is much shorter than tradition algorithms and the precision is relatively improved. The results show that the improved algorithm effectively reduces the training fluctuation and improves the speed. The optimum result could more easily get
Keywords :
power engineering computing; power generation control; power markets; recurrent neural nets; BP neural network; competition competence evaluation; computation time; dynamic controlling quotients; electricity market; feedback lag; local optimal minimum; power generating enterprises; Automation; Character generation; Electricity supply industry; Electronic mail; Fluctuations; Intelligent control; Neural networks; Neurofeedback; Power generation; Sun; dynamic control; enterprise competition competence; evaluation index; improved BP neural network;
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
DOI :
10.1109/WCICA.2006.1712908