Captive balloon wind speed prediction method and system
The invention discloses a captive balloon wind speed prediction method and system. According to the invention, training is carried out through the LSTM model to construct the relationship between the measurement data acquired by the captive balloon wind measurement device and the wind speed measured...
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| creator | WAKI XIA HAILONG ZHANG CONG LI JUN ZHANG MAN ZHAO FENG LU HENGZHI WANG JIALE YU GUANGYU WANG HAO XI ZICHEN LING ZIXING |
| description | The invention discloses a captive balloon wind speed prediction method and system. According to the invention, training is carried out through the LSTM model to construct the relationship between the measurement data acquired by the captive balloon wind measurement device and the wind speed measured by the anemometer, and the wind speed prediction result can be obtained only by inputting the measurement data acquired by the captive balloon wind measurement device into the trained LSTM model in the measurement process without building a measurement environment of the anemometer. According to the method, the LSTM model does not need to be constructed, a mechanical model and a mechanical balance model do not need to be constructed, and data noise reduction is performed in combination with the WTD algorithm, so that the LSTM model has relatively high anti-noise capability, and the prediction result of the LSTM model has relatively high prediction precision. According to the invention, the precision of wind speed |
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According to the invention, training is carried out through the LSTM model to construct the relationship between the measurement data acquired by the captive balloon wind measurement device and the wind speed measured by the anemometer, and the wind speed prediction result can be obtained only by inputting the measurement data acquired by the captive balloon wind measurement device into the trained LSTM model in the measurement process without building a measurement environment of the anemometer. According to the method, the LSTM model does not need to be constructed, a mechanical model and a mechanical balance model do not need to be constructed, and data noise reduction is performed in combination with the WTD algorithm, so that the LSTM model has relatively high anti-noise capability, and the prediction result of the LSTM model has relatively high prediction precision. According to the invention, the precision of wind speed</description><language>chi ; eng</language><subject>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 ; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT ; MEASURING ; MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION,OR SHOCK ; METEOROLOGY ; PHYSICS ; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR ; TESTING</subject><creationdate>2023</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20230530&DB=EPODOC&CC=CN&NR=116187568A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25563,76418</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20230530&DB=EPODOC&CC=CN&NR=116187568A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>WAKI</creatorcontrib><creatorcontrib>XIA HAILONG</creatorcontrib><creatorcontrib>ZHANG CONG</creatorcontrib><creatorcontrib>LI JUN</creatorcontrib><creatorcontrib>ZHANG MAN</creatorcontrib><creatorcontrib>ZHAO FENG</creatorcontrib><creatorcontrib>LU HENGZHI</creatorcontrib><creatorcontrib>WANG JIALE</creatorcontrib><creatorcontrib>YU GUANGYU</creatorcontrib><creatorcontrib>WANG HAO</creatorcontrib><creatorcontrib>XI ZICHEN</creatorcontrib><creatorcontrib>LING ZIXING</creatorcontrib><title>Captive balloon wind speed prediction method and system</title><description>The invention discloses a captive balloon wind speed prediction method and system. According to the invention, training is carried out through the LSTM model to construct the relationship between the measurement data acquired by the captive balloon wind measurement device and the wind speed measured by the anemometer, and the wind speed prediction result can be obtained only by inputting the measurement data acquired by the captive balloon wind measurement device into the trained LSTM model in the measurement process without building a measurement environment of the anemometer. According to the method, the LSTM model does not need to be constructed, a mechanical model and a mechanical balance model do not need to be constructed, and data noise reduction is performed in combination with the WTD algorithm, so that the LSTM model has relatively high anti-noise capability, and the prediction result of the LSTM model has relatively high prediction precision. 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According to the invention, training is carried out through the LSTM model to construct the relationship between the measurement data acquired by the captive balloon wind measurement device and the wind speed measured by the anemometer, and the wind speed prediction result can be obtained only by inputting the measurement data acquired by the captive balloon wind measurement device into the trained LSTM model in the measurement process without building a measurement environment of the anemometer. According to the method, the LSTM model does not need to be constructed, a mechanical model and a mechanical balance model do not need to be constructed, and data noise reduction is performed in combination with the WTD algorithm, so that the LSTM model has relatively high anti-noise capability, and the prediction result of the LSTM model has relatively high prediction precision. According to the invention, the precision of wind speed</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 INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT MEASURING MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION,OR SHOCK METEOROLOGY PHYSICS SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR TESTING |
| title | Captive balloon wind speed prediction method and system |
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