Power carbon emission prediction method and device based on integrated learning module
The invention discloses a power carbon emission prediction method and device based on an integrated learning module, features irrelevant to power data can be removed by obtaining historical power carbon emission data and performing correlation analysis on the historical carbon emission data, the num...
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| creator | LIN KEYAO ZENG ZHENSONG SHEN YU QUE DINGFEI LIN WENBIN LIU LIN YANG SIYU LIN WEIWEI TU XIAZHE |
| description | The invention discloses a power carbon emission prediction method and device based on an integrated learning module, features irrelevant to power data can be removed by obtaining historical power carbon emission data and performing correlation analysis on the historical carbon emission data, the number of features in a data set is reduced, and the prediction accuracy of the power carbon emission is improved by performing standardization processing on the data. Influences caused by different dimensions or different value ranges among data features are eliminated, finally, multiple groups of predicted values are obtained through different base learners, and then final output is realized through a meta learner, so that the problems of inaccurate models and the like existing in power carbon emission prediction can be effectively solved. Therefore, the workload of related workers is effectively reduced, and the method has a very strong expansion characteristic.
本发明公开一种基于集成学习模块的电力碳排放预测方法及设备，通过获取历史电力碳排放数据后，对历史碳排放数据进 |
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本发明公开一种基于集成学习模块的电力碳排放预测方法及设备，通过获取历史电力碳排放数据后，对历史碳排放数据进</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 ; PHYSICS ; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</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=20230512&DB=EPODOC&CC=CN&NR=116108963A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25562,76317</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20230512&DB=EPODOC&CC=CN&NR=116108963A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>LIN KEYAO</creatorcontrib><creatorcontrib>ZENG ZHENSONG</creatorcontrib><creatorcontrib>SHEN YU</creatorcontrib><creatorcontrib>QUE DINGFEI</creatorcontrib><creatorcontrib>LIN WENBIN</creatorcontrib><creatorcontrib>LIU LIN</creatorcontrib><creatorcontrib>YANG SIYU</creatorcontrib><creatorcontrib>LIN WEIWEI</creatorcontrib><creatorcontrib>TU XIAZHE</creatorcontrib><title>Power carbon emission prediction method and device based on integrated learning module</title><description>The invention discloses a power carbon emission prediction method and device based on an integrated learning module, features irrelevant to power data can be removed by obtaining historical power carbon emission data and performing correlation analysis on the historical carbon emission data, the number of features in a data set is reduced, and the prediction accuracy of the power carbon emission is improved by performing standardization processing on the data. Influences caused by different dimensions or different value ranges among data features are eliminated, finally, multiple groups of predicted values are obtained through different base learners, and then final output is realized through a meta learner, so that the problems of inaccurate models and the like existing in power carbon emission prediction can be effectively solved. Therefore, the workload of related workers is effectively reduced, and the method has a very strong expansion characteristic.
本发明公开一种基于集成学习模块的电力碳排放预测方法及设备，通过获取历史电力碳排放数据后，对历史碳排放数据进</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES</subject><subject>PHYSICS</subject><subject>SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2023</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNijsKAjEURdNYiLqH5wIEw8CgpQyKlViI7fAmuc4E8iOJun0juACrcw73zsX9Gt5IpDgNwROcydlUiQnaqPJVhzIFTew1abyMAg2coalOxheMiUstC07e-JFc0E-LpZg92GasflyI9el4684bxNAjR1bwKH13kbKV292-bQ7NP58PMrI5ug</recordid><startdate>20230512</startdate><enddate>20230512</enddate><creator>LIN KEYAO</creator><creator>ZENG ZHENSONG</creator><creator>SHEN YU</creator><creator>QUE DINGFEI</creator><creator>LIN WENBIN</creator><creator>LIU LIN</creator><creator>YANG SIYU</creator><creator>LIN WEIWEI</creator><creator>TU XIAZHE</creator><scope>EVB</scope></search><sort><creationdate>20230512</creationdate><title>Power carbon emission prediction method and device based on integrated learning module</title><author>LIN KEYAO ; ZENG ZHENSONG ; SHEN YU ; QUE DINGFEI ; LIN WENBIN ; LIU LIN ; YANG SIYU ; LIN WEIWEI ; TU XIAZHE</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN116108963A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2023</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES</topic><topic>PHYSICS</topic><topic>SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</topic><toplevel>online_resources</toplevel><creatorcontrib>LIN KEYAO</creatorcontrib><creatorcontrib>ZENG ZHENSONG</creatorcontrib><creatorcontrib>SHEN YU</creatorcontrib><creatorcontrib>QUE DINGFEI</creatorcontrib><creatorcontrib>LIN WENBIN</creatorcontrib><creatorcontrib>LIU LIN</creatorcontrib><creatorcontrib>YANG SIYU</creatorcontrib><creatorcontrib>LIN WEIWEI</creatorcontrib><creatorcontrib>TU XIAZHE</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>LIN KEYAO</au><au>ZENG ZHENSONG</au><au>SHEN YU</au><au>QUE DINGFEI</au><au>LIN WENBIN</au><au>LIU LIN</au><au>YANG SIYU</au><au>LIN WEIWEI</au><au>TU XIAZHE</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Power carbon emission prediction method and device based on integrated learning module</title><date>2023-05-12</date><risdate>2023</risdate><abstract>The invention discloses a power carbon emission prediction method and device based on an integrated learning module, features irrelevant to power data can be removed by obtaining historical power carbon emission data and performing correlation analysis on the historical carbon emission data, the number of features in a data set is reduced, and the prediction accuracy of the power carbon emission is improved by performing standardization processing on the data. Influences caused by different dimensions or different value ranges among data features are eliminated, finally, multiple groups of predicted values are obtained through different base learners, and then final output is realized through a meta learner, so that the problems of inaccurate models and the like existing in power carbon emission prediction can be effectively solved. Therefore, the workload of related workers is effectively reduced, and the method has a very strong expansion characteristic.
本发明公开一种基于集成学习模块的电力碳排放预测方法及设备，通过获取历史电力碳排放数据后，对历史碳排放数据进</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 PHYSICS SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR |
| title | Power carbon emission prediction method and device based on integrated learning module |
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