Improved cellular automaton cyanobacterial bloom prediction method
The invention discloses an improved cellular automaton cyanobacterial bloom prediction method, which comprises the following steps: firstly, inverting concentrations of N and P elements in a water body by using MODIS data, and then applying a result to an analytic hierarchy process (AHP) model. And...
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| creator | ZHANG MAOLIN GAO ZUYU TANG YIDAN WANG XINRUI WANG ZHANCHU LUAN GUIZE ZHAO FEI ZHANG SUJIN ZHANG YIYANG ZHU SHAOTING SUN YONGQI ZHANG XINGYI WU YIHAN LIN DANNI ZHONG ZHENHUA IWAKYO ZHAO ZHIFANG |
| description | The invention discloses an improved cellular automaton cyanobacterial bloom prediction method, which comprises the following steps: firstly, inverting concentrations of N and P elements in a water body by using MODIS data, and then applying a result to an analytic hierarchy process (AHP) model. And 3, establishing a diffusion potential index, and predicting the distribution of blue-green algae by using a cellular automaton model. Results show that the method can effectively predict the dynamic change of the blue-green algae from outbreak to diffusion in a short time. The model aims to solve the problem that cyanobacteria detection focuses on the formation mechanism of the cyanobacteria at present, and the cyanobacteria is rarely dynamically monitored, an improved cellular automaton cyanobacteria bloom prediction model is provided, the model effectively predicts dynamic transfer of the cyanobacteria from outbreak to diffusion in a short time, and help is provided for decision makers to monitor lake health.
本发明 |
| format | Patent |
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And 3, establishing a diffusion potential index, and predicting the distribution of blue-green algae by using a cellular automaton model. Results show that the method can effectively predict the dynamic change of the blue-green algae from outbreak to diffusion in a short time. The model aims to solve the problem that cyanobacteria detection focuses on the formation mechanism of the cyanobacteria at present, and the cyanobacteria is rarely dynamically monitored, an improved cellular automaton cyanobacteria bloom prediction model is provided, the model effectively predicts dynamic transfer of the cyanobacteria from outbreak to diffusion in a short time, and help is provided for decision makers to monitor lake health.
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| 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 INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS PHYSICS SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR |
| title | Improved cellular automaton cyanobacterial bloom prediction method |
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