Mountain torrent disaster risk early warning method integrating binary statistics and machine learning

• Main Authors: YANG LULU, YANG YU, ZHU WEN, LIAO MEIYU, FANG XIUQIN
• Format: Patent
• Language: Chinese; English
• Published: 09.07.2024
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; PHYSICS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

The invention discloses a mountain torrent disaster risk early warning method integrating binary statistics and machine learning. The mountain torrent disaster risk early warning method is characterized by comprising the following steps: step 1, constructing a mountain torrent disaster index system; 2, calculating the mountain torrent disaster degree by using historical disaster data; 3, analyzing the interval sensitivity of the mountain torrent disaster risk factors by applying the determination coefficient CF; step 4, performing merging calculation according to the CF values of all the factors and all the intervals to obtain a comprehensive action value between a single factor and a plurality of factors, and calculating the weight of each factor according to the comprehensive action value; 5, constructing a machine learning regression model by taking the mountain torrent disaster degree as a predicted value and taking the product of the interval sensitivity and the factor weight value of the mountain torren