Abstract
BP neural network is a kind of prediction method, but it has some disadvantages. So an improved particle swarm optimization scheme is used to optimize neural network parameters and structure. Both training convergence speed and classification accuracy is improved. Interest rate is always the focus in the economic research. The proposed scheme is used for seven days interbank offered rate prediction in China and the result shows that the BP neural network based on improved PSO has higher accuracy than the BP algorithm, which can provide important reference for central bank to work out monetary policy.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
