The network loan risk prediction model based on convolutional neural network and Stacking fusion model

2021 ◽  
pp. 107961
Author(s):  
Meixuan Li ◽  
Chun Yan ◽  
Wei Liu
Keyword(s):  
Neural Network ◽  
Prediction Model ◽  
Convolutional Neural Network ◽  
Risk Prediction ◽  
Risk Prediction Model ◽  
Fusion Model ◽  
Model Based ◽  
Loan Risk

scholarly journals Tax Risk Prediction of Real Estate Based on Convolutional Neural Network

2021 ◽  
Author(s):  
Meilin Yin ◽  
Ning Luo
Keyword(s):  
Neural Network ◽  
Risk Management ◽  
Real Estate ◽  
Prediction Model ◽  
Convolutional Neural Network ◽  
Risk Prediction ◽  
Risk Identification ◽  
Risk Prediction Model ◽  
The Real Estate ◽  
The Times

Risk management is an important link in tax administration. From China’s taxation practice, risk identification has become the weakness of tax management. With the complexity of massive data and the secrecy of modern transactions, traditional tax risk identification can no longer adapt to the development of the times. In the past, most risk researches focused on the basic machine learning stage. There are gaps in the application of deep learning in tax risk management. Based on the tax risk management indicators, this paper took the real estate industry as an example. We used convolutional neural network (CNN) to construct a tax risk prediction model. The experiment shows that a tax risk prediction model based on CNN has higher accuracy in tax risk identification and has a stronger ability to process tax data. The model has a certain reference value for tax authorities to reduce tax risk and tax loss.

scholarly journals Construction project risk prediction model based on EW-FAHP and one dimensional convolution neural network

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0246539
Author(s):  
Yawen Zhong ◽  
Hailing Li ◽  
Leilei Chen
Keyword(s):  
Neural Network ◽  
Prediction Model ◽  
Risk Prediction ◽  
Construction Project ◽  
Risk Prediction Model ◽  
Convolution Neural Network ◽  
Project Risk ◽  
Construction Period ◽  
One Dimensional ◽  
Model Based

In order to solve the problem of low accuracy of traditional construction project risk prediction, a project risk prediction model based on EW-FAHP and 1D-CNN(One Dimensional Convolution Neural Network) is proposed. Firstly, the risk evaluation index value of construction project is selected by literature analysis method, and the comprehensive weight of risk index is obtained by combining entropy weight method (EW) and fuzzy analytic hierarchy process (FAHP). The risk weight is input into the 1D-CNN model for training and learning, and the prediction values of construction period risk and cost risk are output to realize the risk prediction. The experimental results show that the average absolute error of the construction period risk and cost risk of the risk prediction model proposed in this paper is below 0.1%, which can meet the risk prediction of construction projects with high accuracy.

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