Reloading scheme search optimization method
The invention relates to a refueling and loading scheme search optimization method. The method comprises the following steps: S1, generating a plurality of common new component layouts according to a plurality of historical refueling schemes; obtaining old component information in the historical ref...
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| creator | HUANG JIE HAN SONG ZHANG HONG YANG SHUOYAN PENG SITAO LI JINGGANG YAO JIANFAN UMAKURA WEI JINFENG |
| description | The invention relates to a refueling and loading scheme search optimization method. The method comprises the following steps: S1, generating a plurality of common new component layouts according to a plurality of historical refueling schemes; obtaining old component information in the historical refueling scheme, and generating an old component database; s2, selecting old components from an old component database according to the common new component layout, randomly loading the old components into the common new component layout to generate K loading schemes, and selecting K1 loading schemes from the K loading schemes to form training samples; wherein K1lt; k; s3, training by using the training sample to generate a prediction model library meeting a precision requirement; the prediction model library contains a plurality of key parameter prediction models; and S4, selecting a key parameter prediction model corresponding to the refueling notification information from the prediction model library according to |
| format | Patent |
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The method comprises the following steps: S1, generating a plurality of common new component layouts according to a plurality of historical refueling schemes; obtaining old component information in the historical refueling scheme, and generating an old component database; s2, selecting old components from an old component database according to the common new component layout, randomly loading the old components into the common new component layout to generate K loading schemes, and selecting K1 loading schemes from the K loading schemes to form training samples; wherein K1lt; k; s3, training by using the training sample to generate a prediction model library meeting a precision requirement; the prediction model library contains a plurality of key parameter prediction models; and S4, selecting a key parameter prediction model corresponding to the refueling notification information from the prediction model library according to</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 ; NUCLEAR ENGINEERING ; NUCLEAR PHYSICS ; NUCLEAR REACTORS ; PHYSICS ; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</subject><creationdate>2022</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=20220329&DB=EPODOC&CC=CN&NR=114254803A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,309,781,886,25569,76552</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20220329&DB=EPODOC&CC=CN&NR=114254803A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>HUANG JIE</creatorcontrib><creatorcontrib>HAN SONG</creatorcontrib><creatorcontrib>ZHANG HONG</creatorcontrib><creatorcontrib>YANG SHUOYAN</creatorcontrib><creatorcontrib>PENG SITAO</creatorcontrib><creatorcontrib>LI JINGGANG</creatorcontrib><creatorcontrib>YAO JIANFAN</creatorcontrib><creatorcontrib>UMAKURA</creatorcontrib><creatorcontrib>WEI JINFENG</creatorcontrib><title>Reloading scheme search optimization method</title><description>The invention relates to a refueling and loading scheme search optimization method. 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The method comprises the following steps: S1, generating a plurality of common new component layouts according to a plurality of historical refueling schemes; obtaining old component information in the historical refueling scheme, and generating an old component database; s2, selecting old components from an old component database according to the common new component layout, randomly loading the old components into the common new component layout to generate K loading schemes, and selecting K1 loading schemes from the K loading schemes to form training samples; wherein K1lt; k; s3, training by using the training sample to generate a prediction model library meeting a precision requirement; the prediction model library contains a plurality of key parameter prediction models; and S4, selecting a key parameter prediction model corresponding to the refueling notification information from the prediction model library according to</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 NUCLEAR ENGINEERING NUCLEAR PHYSICS NUCLEAR REACTORS PHYSICS SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR |
| title | Reloading scheme search optimization method |
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