Satellite task planning scheme evaluation method based on deep learning
The invention discloses a satellite task planning scheme evaluation method based on deep learning, and belongs to the technical field of satellite task planning. The method specifically comprises the steps of satellite task planning scheme historical data acquisition, data preprocessing, sample set...
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| creator | XING YING ZHU JIN WANG GANG CHEN JINYONG ZHU GUANGXI CHAI YINGTE MIAO SHAOBO ZHANG CHAO |
| description | The invention discloses a satellite task planning scheme evaluation method based on deep learning, and belongs to the technical field of satellite task planning. The method specifically comprises the steps of satellite task planning scheme historical data acquisition, data preprocessing, sample set construction, evaluation model establishment, model training and verification, planning scheme real-time evaluation and the like. According to the satellite task planning scheme historical data acquisition, executed satellite observation tasks and planning schemes are integrated; the data preprocessing step is used for realizing normalization processing of the acquired data; in the sample set construction step, an index system is constructed, a combination weight is calculated, a historical planning scheme score is obtained, then a data set containing evaluation index data and the scheme score is formed, and a training set and a test set are divided. Compared with a traditional satellite task planning scheme evalua |
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The method specifically comprises the steps of satellite task planning scheme historical data acquisition, data preprocessing, sample set construction, evaluation model establishment, model training and verification, planning scheme real-time evaluation and the like. According to the satellite task planning scheme historical data acquisition, executed satellite observation tasks and planning schemes are integrated; the data preprocessing step is used for realizing normalization processing of the acquired data; in the sample set construction step, an index system is constructed, a combination weight is calculated, a historical planning scheme score is obtained, then a data set containing evaluation index data and the scheme score is formed, and a training set and a test set are divided. 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The method specifically comprises the steps of satellite task planning scheme historical data acquisition, data preprocessing, sample set construction, evaluation model establishment, model training and verification, planning scheme real-time evaluation and the like. According to the satellite task planning scheme historical data acquisition, executed satellite observation tasks and planning schemes are integrated; the data preprocessing step is used for realizing normalization processing of the acquired data; in the sample set construction step, an index system is constructed, a combination weight is calculated, a historical planning scheme score is obtained, then a data set containing evaluation index data and the scheme score is formed, and a training set and a test set are divided. 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| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING PHYSICS |
| title | Satellite task planning scheme evaluation method based on deep learning |
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