The Ship Collision Accidents Based on Logistic Regression and Big Data

In this paper, the formation of a collision accident, especially the human factors, is partially refined into the more detailed factors causing the collision, and the maximum impact factors are obtained by using Logistic analysis. The Logistic Ordered Multiple Regression in Regression Analysis is applied to the study of the causes of ship collision. The main causes of accidents in a period of time are revealed and forecasted by Logistic Ordered Multiple Regression, and the supervision of its behavior is strengthened to reduce the occurrence of collision accidents. The results show that logistic regression analysis can complete the analysis and early warning of the main impact factors of accidents.