Multi-classification assessment of bank personal credit risk based on multi-source information fusion

2021 ◽  
pp. 116236
Author(s):  
Tianhui Wang ◽  
Renjing Liu ◽  
Guohua Qi
Keyword(s):  
Credit Risk ◽  
Information Fusion ◽  
Source Information ◽  
Personal Credit ◽  
Multi Classification

Credit Risk Management for College Students: An Analysis of Influencing Factors Based on 5C Approach

2021 ◽  
Vol 12 (1) ◽  
pp. 105-105
Author(s):  
Xiang Zou ◽  
Jinting Zhao ◽  
Yun Tong
Keyword(s):  
College Students ◽  
Risk Management ◽  
Credit Risk ◽  
Evaluation System ◽  
Least Squares Method ◽  
Credit Risk Management ◽  
Credit Evaluation ◽  
Personal Credit ◽  
Depth Analysis ◽  
Credit Evaluation System

This paper focuses on the construction of college students' credit evaluation system and credit risk management under the background of big data. Firstly, based on the 5C approach, this paper evaluates the personal credit of college students from 5 dimensions and 24 indicators, which finally contribute to the establishment of the credit evaluation system for college students. Then, the partial least squares method is used to build the structural equation model to evaluate the effectiveness of the credit evaluation system for college students. According to the in-depth analysis of PSL-SEM, the factors that affect the credit risk of college students are effectively evaluated, and it has contributed to the establishment and improvement of the credit system of college students. Keywords: Personal Credit, Credit Evaluation, Credit Risk, 5C Approach, PLS-SEM.

scholarly journals STUDY ON CARDIOVASCULAR MONITORING AND DIAGNOSIS OF ATHLETES

2021 ◽  
Vol 27 (8) ◽  
pp. 822-825
Author(s):  
Zhangbo Xiao ◽  
Chang Sun ◽  
Jie Bai ◽  
Xingjiang Li
Keyword(s):  
Information Fusion ◽  
High Intensity ◽  
Heart Function ◽  
Elite Athletes ◽  
Monitoring And Evaluation ◽  
Control Group ◽  
Cardiovascular Monitoring ◽  
Source Information ◽  
Level Of Evidence ◽  
Sinus Arrhythmia

ABSTRACT Introduction: The study and collection of athletes’ heart function index parameters and the correct and reasonable evaluation of body functions can effectively adjust training plans and avoid athletes’ bodily exhaustion. Objective: To study the diagnosis of myocardial injury by cardiovascular monitoring in athletes from two aspects: extraction of characteristic parameters of heart function and research of signal processing. Methods: The heart function intelligent evaluation algorithm was studied by using multi-source information fusion, and embedded technology; miniature sensors were used as well. Results: The incidence of severe ventricular arrhythmia was lower in both groups. The incidence of sinus arrhythmia and intermittent second degree I atrioventricular block in the high-intensity group was significantly higher than that in the control group. The number of atrial and ventricular premature beats was lower in the control group, but increased significantly in the high-intensity group. Conclusions: This study applied the theory of multi-source information fusion to carry out representative research on the intelligent monitoring and evaluation of the heart function of elite athletes, centering on the application requirements of the heart function monitoring of elite athletes. Level of evidence II; Therapeutic studies - investigation of treatment results.

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