Innovative Decision and Forecasting Approach on Navigation Risk

Abstract

In view to the unstable navigation risk assessment and make the future navigation risk forecasting, an innovative decision and forecasting approach is put forward in this study. Different from the existing literature, at the current time step, we first deduce an enhanced evidence combination rule to integrate uncertain and conflicting evidences by using weighted basic probabilistic assignment and matrix operation. As a result, a stable decision is effectively achieved no matter what characteristics of the available evidences are. Further, an improved α-β filter is designed with its adaptive coefficients in the novel filtering framework in order to forecast the future navigation risk. What's more, it is an excellent communication between the combined basic probabilistic assignment and the improved α-β filter for the first time. After the deep analysis of the computational complexity, a plenty of numeric simulations and actual experiments are provided to indicate the reliability and efficiency of the proposed approach.

Keywords

• Navigation risk
• combination rule
• decision
• forecasting
• computational complexity