Earticle

초록

영어

Aimed at the highly nonlinear and uncertainty of gold price changes, a new method for gold price predition based on improved PSO-BP is proposed. By introducing mutation operation and adaptive adjust of inertia weight , the problem of easy to fall into local optimum, premature, low precision and low later interation efficiency of PSO are solved. By using the improved PSO to optimiaze BP neural network’s parameters, the learning rate and optimization capability of conventional BP are effectively improved. The simulation results of gold price prediction show that the predict accuracy of the new method is significantly higher than that of conventional BP neural network and wavelet neural network method. And the method is effective and feasible.

목차

Abstract
 1. Introduction
 2. BP Neural Network
 3. PSO Algorithm and its Improvement
  3.1. Standard PSO Algorithm
  3.2. The Improvement of PSO
  3.3. The Improved PSO-BP Network
 4. Gold Price Prediction based on Improved
 5. Conclusion
 References

키워드

저자

• Yan Wang [ Dept. of computer, North China Electric Power University, Baoding, Hebei, 071003, China ] Corresponding Author
• Liguo Zhang [ College of Information Science & Technology, Agricultural University of Hebei Hebei Baoding, 071001, China ]
• Yongfu Liu [ College of Information Science & Technology, Agricultural University of Hebei Hebei Baoding, 071001, China ]
• Jun Guo [ Dept. of computer, North China Electric Power University, Baoding, Hebei, 071003, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of u- and e- Service, Science and Technology

• 간기

  격월간

• pISSN

  2005-4246

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605