Research on Enterprise Financial Customer Classification Method and Preference Based on Intelligent Algorithm. (28th November 2021)
- Record Type:
- Journal Article
- Title:
- Research on Enterprise Financial Customer Classification Method and Preference Based on Intelligent Algorithm. (28th November 2021)
- Main Title:
- Research on Enterprise Financial Customer Classification Method and Preference Based on Intelligent Algorithm
- Authors:
- Fu, Ze
Zhang, Bo
Ou, Lingjun
Sun, Kaiyang
Sun, Xinyi
Chen, Ningyan - Other Names:
- Gupta Deepak Academic Editor.
- Abstract:
- Abstract : Compared with the past questionnaire survey, this paper applies the intelligent algorithm developed rapidly in recent years to identify the tendency of customers to buy financial products in the market. In addition, for the single state customer classification indicators based on the previous demographic information and action information, it is proposed to combine the action of market activities with demographic information; that is, the static integrated customer classification index is further combined with the improved neural network model to study the classification and preference of enterprise financial customers. Firstly, the enterprise financial customer classification model based on neural network algorithm is studied. Aiming at the shortcomings of easy falling into the local optimal solution of neural network algorithm, slow convergence speed of algorithm, and difficult setting of network structure, combined with the characteristics of genetic algorithm, the concept of adaptive genetic neural network algorithm is proposed. Then, the design of adaptive genetic neural network model is studied. Secondly, combined with the customer data of a financial enterprise and the characteristics of enterprise finance, this paper analyzes the risk influencing factors of enterprise financial customers, analyzes the customer data, evaluates the enterprise financial customers through the adaptive genetic neural network model, and realizes the classification of enterpriseAbstract : Compared with the past questionnaire survey, this paper applies the intelligent algorithm developed rapidly in recent years to identify the tendency of customers to buy financial products in the market. In addition, for the single state customer classification indicators based on the previous demographic information and action information, it is proposed to combine the action of market activities with demographic information; that is, the static integrated customer classification index is further combined with the improved neural network model to study the classification and preference of enterprise financial customers. Firstly, the enterprise financial customer classification model based on neural network algorithm is studied. Aiming at the shortcomings of easy falling into the local optimal solution of neural network algorithm, slow convergence speed of algorithm, and difficult setting of network structure, combined with the characteristics of genetic algorithm, the concept of adaptive genetic neural network algorithm is proposed. Then, the design of adaptive genetic neural network model is studied. Secondly, combined with the customer data of a financial enterprise and the characteristics of enterprise finance, this paper analyzes the risk influencing factors of enterprise financial customers, analyzes the customer data, evaluates the enterprise financial customers through the adaptive genetic neural network model, and realizes the classification of enterprise financial customers. Through an example, it is proved that the enterprise financial customer classification and preference model based on the adaptive genetic neural network algorithm discussed in this paper has better customer classification accuracy and can provide better method support for enterprise financial customer management. … (more)
- Is Part Of:
- Wireless communications and mobile computing. Volume 2021(2021)
- Journal:
- Wireless communications and mobile computing
- Issue:
- Volume 2021(2021)
- Issue Display:
- Volume 2021, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 2021
- Issue:
- 2021
- Issue Sort Value:
- 2021-2021-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-11-28
- Subjects:
- Wireless communication systems -- Periodicals
Mobile communication systems -- Periodicals
621.38205 - Journal URLs:
- https://onlinelibrary.wiley.com/journal/15308677 ↗
https://www.hindawi.com/journals/wcmc/ ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1155/2021/6585486 ↗
- Languages:
- English
- ISSNs:
- 1530-8669
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 9323.860000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 20157.xml