scholarly journals A Policy Category Analysis Model for Tourism Promotion in China During the COVID-19 Pandemic Based on Data Mining and Binary Regression

2020 ◽  
Vol Volume 13 ◽  
pp. 3211-3233
Author(s):  
Tinggui Chen ◽  
Lijuan Peng ◽  
Xiaohua Yin ◽  
Bailu Jing ◽  
Jianjun Yang ◽  
...  
Keyword(s):  
Data Mining ◽  
Analysis Model ◽  
Binary Regression ◽  
Tourism Promotion

Application of data mining technology and wireless network sensing technology in sports training index analysis

2020 ◽  
Author(s):  
Liqiu Qian ◽  
Jiatong Liu
Keyword(s):  
Data Mining ◽  
Test Accuracy ◽  
Analysis Method ◽  
Sports Training ◽  
Analysis Model ◽  
Data Types ◽  
Mining Technology ◽  
Accuracy Test ◽  
Index Analysis ◽  
Sensing Technology

Abstract The conventional analysis method can provide a general analysis of sports training index, but its ability is relatively low when analyzing niche data. To solve this problem, this paper proposes data mining technology. First, the indicator parameter classification is determined, then the data mining technology is imported, the sports training analysis mechanism is established through this technology, and the construction of the index analysis model is completed. The model is used to analyze the process of niche data mining, and effective data of training indicators are obtained. Deep learning is a method of machine learning based on representation of data.Through the coverage test, accuracy test and immunity test, the variable parameters of the comprehensive analysis capability are determined. Further calculation of this parameter shows that the comprehensive ability of the data mining application analysis method is improved by 37.14% compared with the conventional method, which is suitable for analysis of niche sports training indicators of different data types.

Data Mining Used for Analyzing the Bankruptcy Risk of the Romanian SMEs

Data Mining ◽  
2013 ◽  
pp. 920-946
Author(s):  
Laura Giurca Vasilescu ◽  
Marian Siminica ◽  
Cerasela Pirvu ◽  
Costel Ionascu ◽  
Anca Mehedintu
Keyword(s):  
Data Mining ◽  
Social Role ◽  
Small And Medium Enterprises ◽  
Warning System ◽  
Analysis Model ◽  
Bankruptcy Risk ◽  
Risk Levels ◽  
Dynamic Economy ◽  
Early Signal ◽  
Medium Enterprises

The small and medium enterprises (SMEs) represent the backbone of the economy, playing a major economic and social role in the process of developing a dynamic economy. But the recent evolutions in the financial markets, the international financial crisis, the increased competition on markets, the lack of financial resources and the insufficient adaptation of many firms to the requests of the European market are new threats which can determine the bankruptcies of the Romanian SMEs. In this context, starting from the necessity to design an early warning system, we will elaborate a new model for analysis of bankruptcy risk for the Romanian SMEs that combine two main categories of indicators: financial ratios and non-financial indicators. The authors’ analysis is based on data mining techniques (CHAID) in order to identify the firms’ categories accordingly to the bankruptcy risk levels. Through the proposed analysis model they try to offer a real surveillance system for the Romanian SMEs which can allow an early signal regarding the bankruptcy risk.

Data Mining Used for Analyzing the Bankruptcy Risk of the Romanian SMEs

2011 ◽  
pp. 144-171
Author(s):  
Laura Giurca Vasilescu ◽  
Marian Siminica ◽  
Cerasela Pirvu ◽  
Costel Ionascu ◽  
Anca Mehedintu
Keyword(s):  
Data Mining ◽  
Social Role ◽  
Small And Medium Enterprises ◽  
Warning System ◽  
Analysis Model ◽  
Bankruptcy Risk ◽  
Risk Levels ◽  
Dynamic Economy ◽  
Early Signal ◽  
Medium Enterprises

The small and medium enterprises (SMEs) represent the backbone of the economy, playing a major economic and social role in the process of developing a dynamic economy. But the recent evolutions in the financial markets, the international financial crisis, the increased competition on markets, the lack of financial resources and the insufficient adaptation of many firms to the requests of the European market are new threats which can determine the bankruptcies of the Romanian SMEs. In this context, starting from the necessity to design an early warning system, we will elaborate a new model for analysis of bankruptcy risk for the Romanian SMEs that combine two main categories of indicators: financial ratios and non-financial indicators. The authors‘ analysis is based on data mining techniques (CHAID) in order to identify the firms’ categories accordingly to the bankruptcy risk levels. Through the proposed analysis model they try to offer a real surveillance system for the Romanian SMEs which can allow an early signal regarding the bankruptcy risk.

Students’ emotional analysis on ideological and political teaching classes based on artificial intelligence and data mining

2020 ◽  
pp. 1-9
Author(s):  
Hou Yuzhong
Keyword(s):  
Artificial Intelligence ◽  
Data Mining ◽  
Analysis Model ◽  
Emotion Analysis ◽  
Artificial Intelligence Technology ◽  
The Individual ◽  
Study Designs ◽  
External Stimuli ◽  
Transfer Probability ◽  
Learning Data

Ideological and political teaching emotion is an important reflection of students’ learning achievements. At present, the effect of emotion analysis of ideological and political students is poor. This article builds on the artificial intelligence technology and combines machine learning data mining ideas to construct a student emotion analysis model in the ideological and political classroom. Starting from the individual, based on the individual’s own emotions and external stimuli, this article carries out emotion transfer probability statistics on the dialogues with emotions marked, and obtains the individual’s emotion transfer matrix. After the corresponding model is constructed, it can be applied to practice, and the research is conducted from the aspects of systematic emotion analysis effect and teaching promotion effect. In addition, this study designs a controlled experiment to analyze the effects of the model. The research results show that the model constructed in this paper has good performance.

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