Earticle

초록

영어

As the value of Big Data was recognized as important, the government, public institutions and private companies began to pay attention to Big Data. Unlike the past, there are diverse data sources, and with the emergence of various planning and analysis techniques based on the convergence of these data, Big Data is sure to become the foundation for the creation of new advanced information and advanced decision-making. This study is to find an alternative to the atmospheric fine dust concentration that is not improved despite various measures. The purpose of this study is to exploit the public data of the Seoul Metropolitan City in order to reduce the air pollution concentration in Seoul. The study was conducted through open source R for Seoul public data analysis. As a result, policy alternatives to activate natural gas vehicles were derived.

목차

Abstract
1. INTRODUCTION
2. THEORETICAL BACKGROUND
2.1. Concept and Constituents of Fine Dust
2.2. Causes of Fine Dust Generation
2.3. Seoul Metropolitan Government Policies for Fine Dust Reduction
3. RESEARCH METHODS AND PROCED
3.1. Problem Definition
3.2. Information Required for the Problem
3.3. Analytical Techniques for Information Extraction and Their Importance
4. DATA COLLECTION AND ANALYSIS
4.1. Data Collection and Preprocessing
4.2. Analysis of the Relationship Between Green Space Quantity and Fine Dust
4.3. Relationship Between Seoul's Vehicle Restriction System and Fine Dust
4.4. Seoul's Natural Gas Buses
4.5. Discussion
5. CONCLUSION
REFERENCES

저자

• Guozhong Li [ Department of MSIS, Kunming University of Science and Technology, Yunnam, China ]
• Seongtaek Park [ Department of MIS, Chungbuk National University, Chungbuk, South Korea ] Corresponding Author

참고문헌