The Fire Risk Prediction for Shipborne Cargo Based on Improved Gray-Markov Model

摘要

Based on the identified fire risk factors of shipborne cargo, data from the wireless sensor network terminals, and the moving-average and unbiased dual-optimized Grey-Markov methods, the real-time risk prediction model is set up, which achieves the quantitative risk. At last, the calculating example improves that the prediction accuracy is improved and the dependency on the historical data is less, which is of instructive significance.