Research and Application of Project Investment Conversion Prediction Based on Improved BP Neural Network

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CIRED 2019 - 758.pdf (599.39 KB)

Paper number

758

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Conference name

CIRED 2019

Conference date

3-6 June 2019

Conference location

Madrid, Spain

Peer-reviewed

Yes

Short title

Convener

Authors

Ru Sen, Fan, State Grid Shanghai Qingpu Electric Power Supply Company, China
Ya, Li, State Grid Shanghai Qingpu Electric Power Supply Company, China
Tao Tao, Ma, State Grid Shanghai Qingpu Electric Power Supply Company, China

Abstract

In order to achieve the goal of "precise investment" and promote the company's operating income and the level of investment management, an improved BP neural network prediction model for project investment conversion is proposed. With fusion of massive online and offline basic data, and generating the model sample data sets, an improved forward BP neural network prediction model is established. When handling the correction error, an additional momentum is added dynamically to adjust the momentum learning rate, so as to speed up the convergence. Based on the predicted project final amount, the rate of project investment conversion can be obtained, and also the probability of predicted value occurrence. The actual test results show that the predicted project final amounts basically fit very well with the actual values, the Mean Absolute Percentage Error is 3.96%.

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Publisher

AIM

Date

2019-06-03

Published in

CIRED 2019 Conference

Permanent link to this record

https://cired-repository.org/handle/20.500.12455/141
http://dx.doi.org/10.34890/284

ISSN

2032-9644

ISBN

978-2-9602415-0-1