scholarly journals Study on Internet Financial Risk Early Warning Based on Big Data Analysis

2015 ◽  
Author(s):  
Yu Shen
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Early Warning ◽  
Financial Risk ◽  
Big Data Analysis

scholarly journals How to Determine the Early Warning Threshold Value of Meteorological Factors on Influenza through Big Data Analysis and Machine Learning

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Hui Ge ◽  
Debao Fan ◽  
Ming Wan ◽  
Lizhu Jin ◽  
Xiaofeng Wang ◽  
...  
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Infectious Diseases ◽  
Early Warning ◽  
Meteorological Factors ◽  
Threshold Value ◽  
Big Data Analysis ◽  
Meteorological Conditions ◽  
Medical Big Data ◽  
Influenza Outbreaks

Infectious diseases are a major health challenge for the worldwide population. Since their rapid spread can cause great distress to the real world, in addition to taking appropriate measures to curb the spread of infectious diseases in the event of an outbreak, proper prediction and early warning before the outbreak of the threat of infectious diseases can provide an important basis for early and reasonable response by the government health sector, reduce morbidity and mortality, and greatly reduce national losses. However, if only traditional medical data is involved, it may be too late or too difficult to implement prediction and early warning of an infectious outbreak. Recently, medical big data has become a research hotspot and has played an increasingly important role in public health, precision medicine, and disease prediction. In this paper, we focus on exploring a prediction and early warning method for influenza with the help of medical big data. It is well known that meteorological conditions have an influence on influenza outbreaks. So, we try to find a way to determine the early warning threshold value of influenza outbreaks through big data analysis concerning meteorological factors. Results show that, based on analysis of meteorological conditions combined with influenza outbreak history data, the early warning threshold of influenza outbreaks could be established with reasonable high accuracy.

scholarly journals Algorithm Design of Early Warning Seatbelt Intelligent Adjustment System Based on Neural Network and Big Data Analysis

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Chunxu Zhou
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Early Warning ◽  
Algorithm Design ◽  
Big Data Analysis ◽  
Design System ◽  
Regulation System ◽  
Hardware System ◽  
Safety Belt ◽  
Adjustment System

With the purpose to guarantee the safety of drivers and passengers as well as lower the death rate collision, the early warning seatbelt intelligent adjustment system is designed by using big data analysis technology based on the aspects of hardware equipment, database, and software program. In the hardware system, microcontroller AT89C52 is applied as the control core. By means of the sensor detection and drive control, the early warning safety belt tightening, locking and lifting, and other functions are realized. Meanwhile, various components of the hardware system are coordinated through debugging several modules in the hardware system and using the modified circuit to connect them together. We determine the relational rules of the database and create the corresponding database table, to provide sufficient data support for the realization of software functions. Using the big data analysis method to process the real-time detection data received by the sensor, the software functions such as timely tightening of safety belt, humidity relaxation, and over-rolling prevention can be realized according to different driving conditions of drivers and vehicles, respectively. The conclusion is drawn through the system test experiment: compared with the traditional regulation system, the design system has a higher degree of regulation, and the application of the design results to the actual vehicle can reduce the crash fatality rate of about 22.4%.

scholarly journals Financial Big Data Analysis and Early Warning Platform: A Case Study

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 36515-36526 ◽  
Author(s):  
Yi Liang ◽  
Daiyong Quan ◽  
Fang Wang ◽  
Xiaojun Jia ◽  
Menggang Li ◽  
...  
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Early Warning ◽  
Big Data Analysis

scholarly journals Internet Financial Risk Early Warning Based on Big Data Analysis

2021 ◽  
pp. 48-60
Author(s):  
Noura Metawa ◽  
◽  
◽  
Saad Metawa
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Prediction Accuracy ◽  
Financial Risk ◽  
Big Data Analysis ◽  
Risk Prevention ◽  
Supervision System ◽  
Finance Industry ◽  
Risk Warning ◽  
Internet Finance

Internet financial risk prevention is an important area for financial risk prevention. In recent years, a series of vicious high-risk events, such as cash lending and P2P platform running, have caused a great negative impact on the reputation of the Internet financial industry, which has aroused great concern from all walks of life. Based on big data analysis technology, this paper constructs an improved algorithm model, and carries out high-precision risk warning for China's Internet financial risk. The forecast data is basically consistent with the actual situation, and the prediction accuracy reaches 90%. It can be seen that the improved model based on the decision tree algorithm has higher prediction accuracy for Internet financial risk warning. This paper systematically sorts out the risks of China's Internet finance from two dimensions: risk type and main risk. And pointed out that the current Internet finance industry in China has a large overall compliance risk, and insufficient infrastructure construction leads to fraud risks. Separate industry supervision has a regulatory vacuum, arbitrage risks are more obvious, and China's financial consumer quality is not high, Internet financial institutions Improper exemption is risky. On this basis, it is proposed to speed up the construction of a multi-integrated Internet financial risk prevention system including the internal risk control system, the industry association self-discipline system, the government administrative supervision system and the effective social supervision system.

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