Title :
Profitability evaluation of the power listed companies based on PSO-BP neural network model
Author :
Sun, Wei ; Zhao, Wei
Author_Institution :
Sch. of Bus. Adm., North China Electr. Power Univ., Baoding, China
Abstract :
In order to make the profitability evaluation of the listed companies more effectively, and provide a basis for decision-making, profitability evaluation model was established in this paper based on particle swarm algorithm (PSO) and the back-propagation algorithm (BP). Then the case study of profitability evaluation of power listed companies in China is proposed. The model takes advantages of the features of global search in PSO and local search in BP neural network. This model not only can find the smallest value in overall situation but also can greatly enhance the running rate. It has been proved by experiment that PSO-BP neural network model obtained a more satisfying effect in profitability evaluation of listed companies.
Keywords :
backpropagation; decision making; electricity supply industry; neural nets; particle swarm optimisation; profitability; China; PSO-BP neural network model; backpropagation algorithm; decision making; global search; local search; particle swarm algorithm; power listed companies; profitability evaluation model; Algebra; Companies; Decision making; Genetic algorithms; Neural networks; Particle swarm optimization; Particle tracking; Profitability; Risk management; Sun; BP Neural Network; Particle Swarm Optimization; Power Listed Companies; Profitability;
Conference_Titel :
Future Computer and Communication (ICFCC), 2010 2nd International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5821-9
DOI :
10.1109/ICFCC.2010.5497824
