Financial production marketing prediction based on optimization GA-BP neural network
The traditional BP neural network has some application problems.For example,the network structure parameter is too dependent on experience and easy to fall into local solution.In order to improve the application defects of BP neural network model,the optimization GA-BP algorithm to optimize BP neura...
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Format: | Article |
Language: | zho |
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Editorial Department of Journal on Communications
2014-11-01
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Series: | Tongxin xuebao |
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Online Access: | http://www.joconline.com.cn/zh/article/doi/10.3969/j.issn.1000-436x.2014.z2.004/ |
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author | Xin JIN Yi-an PAN Jing WU |
author_facet | Xin JIN Yi-an PAN Jing WU |
author_sort | Xin JIN |
collection | DOAJ |
description | The traditional BP neural network has some application problems.For example,the network structure parameter is too dependent on experience and easy to fall into local solution.In order to improve the application defects of BP neural network model,the optimization GA-BP algorithm to optimize BP neural network topology and the selection process of network initial parameter value is proposed.In order to verify the feasibility of the model,marketing customer historical data of a bank short-term financial products as the research object is used to validate the model which could more accurately predict the customer compared with BP neural network model.The test results show that the model could be applied to analysis financial product marketing data and more accurately predict the future marketing results. |
format | Article |
id | doaj-art-97c5a75384384990ac6571f49523ae09 |
institution | Kabale University |
issn | 1000-436X |
language | zho |
publishDate | 2014-11-01 |
publisher | Editorial Department of Journal on Communications |
record_format | Article |
series | Tongxin xuebao |
spelling | doaj-art-97c5a75384384990ac6571f49523ae092025-01-14T06:45:02ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2014-11-0135202559688761Financial production marketing prediction based on optimization GA-BP neural networkXin JINYi-an PANJing WUThe traditional BP neural network has some application problems.For example,the network structure parameter is too dependent on experience and easy to fall into local solution.In order to improve the application defects of BP neural network model,the optimization GA-BP algorithm to optimize BP neural network topology and the selection process of network initial parameter value is proposed.In order to verify the feasibility of the model,marketing customer historical data of a bank short-term financial products as the research object is used to validate the model which could more accurately predict the customer compared with BP neural network model.The test results show that the model could be applied to analysis financial product marketing data and more accurately predict the future marketing results.http://www.joconline.com.cn/zh/article/doi/10.3969/j.issn.1000-436x.2014.z2.004/GA-BPbank promotionoptimization |
spellingShingle | Xin JIN Yi-an PAN Jing WU Financial production marketing prediction based on optimization GA-BP neural network Tongxin xuebao GA-BP bank promotion optimization |
title | Financial production marketing prediction based on optimization GA-BP neural network |
title_full | Financial production marketing prediction based on optimization GA-BP neural network |
title_fullStr | Financial production marketing prediction based on optimization GA-BP neural network |
title_full_unstemmed | Financial production marketing prediction based on optimization GA-BP neural network |
title_short | Financial production marketing prediction based on optimization GA-BP neural network |
title_sort | financial production marketing prediction based on optimization ga bp neural network |
topic | GA-BP bank promotion optimization |
url | http://www.joconline.com.cn/zh/article/doi/10.3969/j.issn.1000-436x.2014.z2.004/ |
work_keys_str_mv | AT xinjin financialproductionmarketingpredictionbasedonoptimizationgabpneuralnetwork AT yianpan financialproductionmarketingpredictionbasedonoptimizationgabpneuralnetwork AT jingwu financialproductionmarketingpredictionbasedonoptimizationgabpneuralnetwork |