The application of the improved BP algorithm in the project investment prediction

  • Jin Dong*
  • , Fajie Wei
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The traditional BP learning algorithm converges slowly, and obviously depends on the step size. The paper has proposed a step-size rule using to improve BP algorithm. In the network training, it can search a relatively reasonable step length in each iteration, so it can reduce the impact of the choice of step length on learning speed greatly. The simulation results of project investment prediction show that the new algorithm is better than the traditional in the iteration time and times.

Original languageEnglish
Title of host publication2nd International Conference on Information Science and Engineering, ICISE2010 - Proceedings
Pages6242-6245
Number of pages4
DOIs
StatePublished - 2010
Event2nd International Conference on Information Science and Engineering, ICISE2010 - Hangzhou, China
Duration: 4 Dec 20106 Dec 2010

Publication series

Name2nd International Conference on Information Science and Engineering, ICISE2010 - Proceedings

Conference

Conference2nd International Conference on Information Science and Engineering, ICISE2010
Country/TerritoryChina
CityHangzhou
Period4/12/106/12/10

Keywords

  • Improved BP algorithm
  • Neural network
  • Project investment prediction
  • Step-size rule

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