Water bloom prediction method based on space-time sequence hybrid model

• Main Authors: ZHANG HUIYAN, WANG LI, XU JIPING, YU JIABIN, WANG XIAOYI, ZHAO ZHIYAO, XIE YUXIN, SUN QIAN
• Format: Patent
• Language: Chinese; English
• Published: 14.01.2020
• 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; ELECTRIC DIGITAL DATA PROCESSING; PHYSICS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

The invention discloses a water bloom prediction method based on a space-time sequence hybrid model, and belongs to the technical field of water environment prediction. The water bloom prediction method comprises the following steps: firstly, extracting a large-scale nonlinear trend term of water bloom spatio-temporal data based on a deep belief network; establishing a space weight matrix based onthe geographic positions of the multivariate space-time meteorological monitoring points; then extracting a small-scale residual term and carrying out modeling again; superposing the large-scale nonlinear trend term prediction value and the small-scale residual term prediction value, and obtaining a meteorological prediction value of the target water area according to an inverse distance weighteddifference method; and using ANFIS fusion to predict the water quality and meteorological data of the target water area. According to the method, the number of influence factors of water bloom outbreak is increased, so that t