Author(s)

Zhiqi Guo, Yi Guan, Jiacong Zhao

Corresponding Author

Zhiqi Guo

Abstract

With the increasing demand for material and cultural life, the holdings of automobiles are increasing day by day, and the per-capita holdings are also decreasing. With the appearance of various traffic problems, traffic accidents frequently occur. It poses a serious threat to the property and life safety of the vast number of residents. The traffic congestion problem has caused many inconveniences to us, delaying a lot of precious time, reducing the happiness index of the people, and solving traditional problems, such as widening roads and increasing traffic. Control personnel, etc., Have not been able to meet the needs of the current stage very well. In recent years, the rise of data mining technology and big data technology has enabled us to see the hope of solving the problem. The rapid development of computer technology and the use of modern hardware technology to collect data have led to a large amount of data collection and processing in many fields. Data mining technology appears in a timely manner, and the generated data is summarized, and a large number of decision-making conclusions are obtained. Traffic pressure has played a big role. Combined with big data technology, the data is fully covered. The sampling method is not used, which makes the data mining conclusion more accurate and more targeted, and achieves accurate problem solving. This paper mainly introduces the Apriori algorithm to process the collected data to find the association rules for traffic accidents, provide decision support for traffic managers, and alleviate various traffic problems that are now emerging.

Keywords

Data mining, Apriori algorithm, Big data, Traffic management