Non-linear regression method for urban power load short-period prediction
The invention relates to a non-linear regression method for urban power load short-period prediction. A relation curve influencing a factor change is drawn; according to industrial, commercial and resident load proportionality coefficients based on statistics, poly-type non-linear composite model ch...
Gespeichert in:
| Hauptverfasser: | , , , |
|---|---|
| Format: | Patent |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | |
|---|---|
| container_issue | |
| container_start_page | |
| container_title | |
| container_volume | |
| creator | CHANG JUNXIAO CHENG JIANGZHOU YOU WENXIA WANG SIYING |
| description | The invention relates to a non-linear regression method for urban power load short-period prediction. A relation curve influencing a factor change is drawn; according to industrial, commercial and resident load proportionality coefficients based on statistics, poly-type non-linear composite model characteristic curves of all loads are obtained by analyses; an accurate multi-element poly-type composite non-linear regression model is obtained; and for the obtained multi-element poly-type composite non-linear regression model, a model prediction value is calculated based on hypothesis testing in mathematical statistics by using a measured load data sample, verification is carried out according to characteristics of all loads obtained by analyses in advance, and determination whether to refuse or accept the model hypothesis is made, thereby obtaining quantitative data related to the model credibility. According to the invention, all factors influencing the load change can be added into the prediction model by using a multi-element regression model; and with the non-linear regression model, defects of the linear regression model can be effectively overcome, thereby improving the prediction precision. |
| format | Patent |
| fullrecord | <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_CN105184388A</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>CN105184388A</sourcerecordid><originalsourceid>FETCH-epo_espacenet_CN105184388A3</originalsourceid><addsrcrecordid>eNqNy7EKwjAURuEsDqK-w_UBApYqZC2lRZdO7iU2f20g5oabiK9vBx_A6Szf2arbwFEHH2GFBE9Bzp4jvVAWdjSz0FseNlLiD4QCW0d5YSk6QfwqksD5qazPXm1mGzIOv-7Use_u7VUj8Yic7ISIMrZDdbpU5lwb09T_mC8GMDUO</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>Non-linear regression method for urban power load short-period prediction</title><source>esp@cenet</source><creator>CHANG JUNXIAO ; CHENG JIANGZHOU ; YOU WENXIA ; WANG SIYING</creator><creatorcontrib>CHANG JUNXIAO ; CHENG JIANGZHOU ; YOU WENXIA ; WANG SIYING</creatorcontrib><description>The invention relates to a non-linear regression method for urban power load short-period prediction. A relation curve influencing a factor change is drawn; according to industrial, commercial and resident load proportionality coefficients based on statistics, poly-type non-linear composite model characteristic curves of all loads are obtained by analyses; an accurate multi-element poly-type composite non-linear regression model is obtained; and for the obtained multi-element poly-type composite non-linear regression model, a model prediction value is calculated based on hypothesis testing in mathematical statistics by using a measured load data sample, verification is carried out according to characteristics of all loads obtained by analyses in advance, and determination whether to refuse or accept the model hypothesis is made, thereby obtaining quantitative data related to the model credibility. According to the invention, all factors influencing the load change can be added into the prediction model by using a multi-element regression model; and with the non-linear regression model, defects of the linear regression model can be effectively overcome, thereby improving the prediction precision.</description><language>eng</language><subject>CALCULATING ; 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>2015</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=20151223&DB=EPODOC&CC=CN&NR=105184388A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25542,76289</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20151223&DB=EPODOC&CC=CN&NR=105184388A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>CHANG JUNXIAO</creatorcontrib><creatorcontrib>CHENG JIANGZHOU</creatorcontrib><creatorcontrib>YOU WENXIA</creatorcontrib><creatorcontrib>WANG SIYING</creatorcontrib><title>Non-linear regression method for urban power load short-period prediction</title><description>The invention relates to a non-linear regression method for urban power load short-period prediction. A relation curve influencing a factor change is drawn; according to industrial, commercial and resident load proportionality coefficients based on statistics, poly-type non-linear composite model characteristic curves of all loads are obtained by analyses; an accurate multi-element poly-type composite non-linear regression model is obtained; and for the obtained multi-element poly-type composite non-linear regression model, a model prediction value is calculated based on hypothesis testing in mathematical statistics by using a measured load data sample, verification is carried out according to characteristics of all loads obtained by analyses in advance, and determination whether to refuse or accept the model hypothesis is made, thereby obtaining quantitative data related to the model credibility. According to the invention, all factors influencing the load change can be added into the prediction model by using a multi-element regression model; and with the non-linear regression model, defects of the linear regression model can be effectively overcome, thereby improving the prediction precision.</description><subject>CALCULATING</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>2015</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNy7EKwjAURuEsDqK-w_UBApYqZC2lRZdO7iU2f20g5oabiK9vBx_A6Szf2arbwFEHH2GFBE9Bzp4jvVAWdjSz0FseNlLiD4QCW0d5YSk6QfwqksD5qazPXm1mGzIOv-7Use_u7VUj8Yic7ISIMrZDdbpU5lwb09T_mC8GMDUO</recordid><startdate>20151223</startdate><enddate>20151223</enddate><creator>CHANG JUNXIAO</creator><creator>CHENG JIANGZHOU</creator><creator>YOU WENXIA</creator><creator>WANG SIYING</creator><scope>EVB</scope></search><sort><creationdate>20151223</creationdate><title>Non-linear regression method for urban power load short-period prediction</title><author>CHANG JUNXIAO ; CHENG JIANGZHOU ; YOU WENXIA ; WANG SIYING</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN105184388A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng</language><creationdate>2015</creationdate><topic>CALCULATING</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>CHANG JUNXIAO</creatorcontrib><creatorcontrib>CHENG JIANGZHOU</creatorcontrib><creatorcontrib>YOU WENXIA</creatorcontrib><creatorcontrib>WANG SIYING</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>CHANG JUNXIAO</au><au>CHENG JIANGZHOU</au><au>YOU WENXIA</au><au>WANG SIYING</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Non-linear regression method for urban power load short-period prediction</title><date>2015-12-23</date><risdate>2015</risdate><abstract>The invention relates to a non-linear regression method for urban power load short-period prediction. A relation curve influencing a factor change is drawn; according to industrial, commercial and resident load proportionality coefficients based on statistics, poly-type non-linear composite model characteristic curves of all loads are obtained by analyses; an accurate multi-element poly-type composite non-linear regression model is obtained; and for the obtained multi-element poly-type composite non-linear regression model, a model prediction value is calculated based on hypothesis testing in mathematical statistics by using a measured load data sample, verification is carried out according to characteristics of all loads obtained by analyses in advance, and determination whether to refuse or accept the model hypothesis is made, thereby obtaining quantitative data related to the model credibility. According to the invention, all factors influencing the load change can be added into the prediction model by using a multi-element regression model; and with the non-linear regression model, defects of the linear regression model can be effectively overcome, thereby improving the prediction precision.</abstract><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | |
| ispartof | |
| issn | |
| language | eng |
| recordid | cdi_epo_espacenet_CN105184388A |
| source | esp@cenet |
| subjects | CALCULATING 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 | Non-linear regression method for urban power load short-period prediction |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-06T06%3A53%3A48IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-epo_EVB&rft_val_fmt=info:ofi/fmt:kev:mtx:patent&rft.genre=patent&rft.au=CHANG%20JUNXIAO&rft.date=2015-12-23&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3ECN105184388A%3C/epo_EVB%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |