Tobacco single leaf weight prediction method based on meteorological coupling soil fertility of big data
The invention discloses a big data-based meteorological coupling soil fertility tobacco single leaf weight prediction method. The method comprises the steps of obtaining meteorological data and soil fertility data in a prediction period; and inputting the meteorological data and the soil fertility d...
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| creator | ZENG LIPING WANG KEMIN WU CHANGHANG PENG YU TAO YONG WU ZHOU WEI BIN MU DONGSHENG CHENG LI XIA XIAOLING WANG XING XU JIAN CHEN LIPING LI XIANG |
| description | The invention discloses a big data-based meteorological coupling soil fertility tobacco single leaf weight prediction method. The method comprises the steps of obtaining meteorological data and soil fertility data in a prediction period; and inputting the meteorological data and the soil fertility data into a single-leaf prediction model, and calculating the single-leaf weight of the tobacco. According to the method, meteorological data and soil fertility data are combined, a Transform model effectively captures a long-distance dependency relationship between input features through a self-attention mechanism, the model can comprehensively understand and utilize interaction between meteorological data and soil data, compared with a traditional statistical prediction model, the method can more accurately predict the weight of a single tobacco leaf, and the method has the advantages that the method is simple and convenient to operate and high in practicability. Therefore, agricultural producers are helped to bet |
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The method comprises the steps of obtaining meteorological data and soil fertility data in a prediction period; and inputting the meteorological data and the soil fertility data into a single-leaf prediction model, and calculating the single-leaf weight of the tobacco. According to the method, meteorological data and soil fertility data are combined, a Transform model effectively captures a long-distance dependency relationship between input features through a self-attention mechanism, the model can comprehensively understand and utilize interaction between meteorological data and soil data, compared with a traditional statistical prediction model, the method can more accurately predict the weight of a single tobacco leaf, and the method has the advantages that the method is simple and convenient to operate and high in practicability. 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The method comprises the steps of obtaining meteorological data and soil fertility data in a prediction period; and inputting the meteorological data and the soil fertility data into a single-leaf prediction model, and calculating the single-leaf weight of the tobacco. According to the method, meteorological data and soil fertility data are combined, a Transform model effectively captures a long-distance dependency relationship between input features through a self-attention mechanism, the model can comprehensively understand and utilize interaction between meteorological data and soil data, compared with a traditional statistical prediction model, the method can more accurately predict the weight of a single tobacco leaf, and the method has the advantages that the method is simple and convenient to operate and high in practicability. 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The method comprises the steps of obtaining meteorological data and soil fertility data in a prediction period; and inputting the meteorological data and the soil fertility data into a single-leaf prediction model, and calculating the single-leaf weight of the tobacco. According to the method, meteorological data and soil fertility data are combined, a Transform model effectively captures a long-distance dependency relationship between input features through a self-attention mechanism, the model can comprehensively understand and utilize interaction between meteorological data and soil data, compared with a traditional statistical prediction model, the method can more accurately predict the weight of a single tobacco leaf, and the method has the advantages that the method is simple and convenient to operate and high in practicability. Therefore, agricultural producers are helped to bet</abstract><oa>free_for_read</oa></addata></record> |
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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 PHYSICS SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR |
| title | Tobacco single leaf weight prediction method based on meteorological coupling soil fertility of big data |
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