Scientific research project budget estimate method based on GA-BP neural network

Guoxin Wang; Yilin Wang; Yan Yan

doi:10.3969/j.issn.0253-374x.2014.08.025

Scientific research project budget estimate method based on GA-BP neural network

Guoxin Wang^*, Yilin Wang, Yan Yan

^*Corresponding author for this work

School of Mechanical Engineering

Beijing Institute of Technology

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

Abstract

An analysis was made of the component and influencing factors of research budget. Then, a research budget estimate model based on Genetic Algorithm-Back Propagation (GA-BP) neural network was built, of which, GA was used to optimize the weights and thresholds of BP neural network. A nonlinear expression between influencing factors (input) and the budget (output) was created. The effectiveness of the method was tested. Test results show the model based on GA-BP neural network is reliable and accurate.

Original language	English
Pages (from-to)	1298-1304
Number of pages	7
Journal	Tongji Daxue Xuebao/Journal of Tongji University
Volume	42
Issue number	8
DOIs	https://doi.org/10.3969/j.issn.0253-374x.2014.08.025
Publication status	Published - 1 Aug 2014

Keywords

Back Propagation (BP) neural network
Budget model
Genetic algorithm
Scientific research project

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10.3969/j.issn.0253-374x.2014.08.025

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abstract = "An analysis was made of the component and influencing factors of research budget. Then, a research budget estimate model based on Genetic Algorithm-Back Propagation (GA-BP) neural network was built, of which, GA was used to optimize the weights and thresholds of BP neural network. A nonlinear expression between influencing factors (input) and the budget (output) was created. The effectiveness of the method was tested. Test results show the model based on GA-BP neural network is reliable and accurate.",

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AB - An analysis was made of the component and influencing factors of research budget. Then, a research budget estimate model based on Genetic Algorithm-Back Propagation (GA-BP) neural network was built, of which, GA was used to optimize the weights and thresholds of BP neural network. A nonlinear expression between influencing factors (input) and the budget (output) was created. The effectiveness of the method was tested. Test results show the model based on GA-BP neural network is reliable and accurate.

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KW - Budget model

KW - Genetic algorithm

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Scientific research project budget estimate method based on GA-BP neural network

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Keywords

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