Customer service risk evaluation system modeling method and system based on artificial intelligence
The invention discloses a customer service risk evaluation system modeling method and system based on artificial intelligence. The method comprises the steps of data collection, data preprocessing, appeal risk evaluation system construction, power failure risk evaluation system construction, load ri...
Gespeichert in:
| Hauptverfasser: | , , , , , , , , , , , , , , |
|---|---|
| Format: | Patent |
| Sprache: | chi ; 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 | YU HONGFU YANG XIAOYAN SU HONGYU MO LIANGYUAN ZHU DI WANG LICHAO HUANG KAI WEI LIUMU WU CHANGSHAN LI LIN FU HUA ZHU NING LIU NA LIAO QIUYUAN HUANG YUSHAN |
| description | The invention discloses a customer service risk evaluation system modeling method and system based on artificial intelligence. The method comprises the steps of data collection, data preprocessing, appeal risk evaluation system construction, power failure risk evaluation system construction, load risk evaluation system construction, value added service risk evaluation system construction and customer service risk evaluation system construction. The invention relates to the technical field of power demand customer service risk prediction, in particular to a customer service risk evaluation system modeling method and system based on artificial intelligence, and the method comprises the steps: carrying out the multi-target data generation through employing a variational automatic encoder, and optimizing the data quality; multiple artificial intelligence models are constructed for prediction, so that prediction errors are reduced; according to the method, prediction results of the three models are superposed, fle |
| format | Patent |
| fullrecord | <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_CN118195302A</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>CN118195302A</sourcerecordid><originalsourceid>FETCH-epo_espacenet_CN118195302A3</originalsourceid><addsrcrecordid>eNqNyrsKwkAQRuE0FqK-w_gAgjEIWkpQrKzsw7j7JxncS9jZBHx7LbS3OsX55oWpR83RI5EiTWJASfRJmNiNnCUG0pdmePLRwknoyCP30RIH-1sPVlj6UE5ZWjHCjiRkOCcdgsGymLXsFKtvF8X6cr7X1w2G2EAHNgjITX0ry0N53Ffb3an6x7wBCak_Lg</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>Customer service risk evaluation system modeling method and system based on artificial intelligence</title><source>esp@cenet</source><creator>YU HONGFU ; YANG XIAOYAN ; SU HONGYU ; MO LIANGYUAN ; ZHU DI ; WANG LICHAO ; HUANG KAI ; WEI LIUMU ; WU CHANGSHAN ; LI LIN ; FU HUA ; ZHU NING ; LIU NA ; LIAO QIUYUAN ; HUANG YUSHAN</creator><creatorcontrib>YU HONGFU ; YANG XIAOYAN ; SU HONGYU ; MO LIANGYUAN ; ZHU DI ; WANG LICHAO ; HUANG KAI ; WEI LIUMU ; WU CHANGSHAN ; LI LIN ; FU HUA ; ZHU NING ; LIU NA ; LIAO QIUYUAN ; HUANG YUSHAN</creatorcontrib><description>The invention discloses a customer service risk evaluation system modeling method and system based on artificial intelligence. The method comprises the steps of data collection, data preprocessing, appeal risk evaluation system construction, power failure risk evaluation system construction, load risk evaluation system construction, value added service risk evaluation system construction and customer service risk evaluation system construction. The invention relates to the technical field of power demand customer service risk prediction, in particular to a customer service risk evaluation system modeling method and system based on artificial intelligence, and the method comprises the steps: carrying out the multi-target data generation through employing a variational automatic encoder, and optimizing the data quality; multiple artificial intelligence models are constructed for prediction, so that prediction errors are reduced; according to the method, prediction results of the three models are superposed, fle</description><language>chi ; eng</language><subject>CALCULATING ; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTINGELECTRIC POWER ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER ; COUNTING ; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES ; ELECTRIC DIGITAL DATA PROCESSING ; ELECTRICITY ; GENERATION ; PHYSICS ; SYSTEMS FOR STORING ELECTRIC ENERGY ; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</subject><creationdate>2024</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=20240614&DB=EPODOC&CC=CN&NR=118195302A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25542,76289</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20240614&DB=EPODOC&CC=CN&NR=118195302A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>YU HONGFU</creatorcontrib><creatorcontrib>YANG XIAOYAN</creatorcontrib><creatorcontrib>SU HONGYU</creatorcontrib><creatorcontrib>MO LIANGYUAN</creatorcontrib><creatorcontrib>ZHU DI</creatorcontrib><creatorcontrib>WANG LICHAO</creatorcontrib><creatorcontrib>HUANG KAI</creatorcontrib><creatorcontrib>WEI LIUMU</creatorcontrib><creatorcontrib>WU CHANGSHAN</creatorcontrib><creatorcontrib>LI LIN</creatorcontrib><creatorcontrib>FU HUA</creatorcontrib><creatorcontrib>ZHU NING</creatorcontrib><creatorcontrib>LIU NA</creatorcontrib><creatorcontrib>LIAO QIUYUAN</creatorcontrib><creatorcontrib>HUANG YUSHAN</creatorcontrib><title>Customer service risk evaluation system modeling method and system based on artificial intelligence</title><description>The invention discloses a customer service risk evaluation system modeling method and system based on artificial intelligence. The method comprises the steps of data collection, data preprocessing, appeal risk evaluation system construction, power failure risk evaluation system construction, load risk evaluation system construction, value added service risk evaluation system construction and customer service risk evaluation system construction. The invention relates to the technical field of power demand customer service risk prediction, in particular to a customer service risk evaluation system modeling method and system based on artificial intelligence, and the method comprises the steps: carrying out the multi-target data generation through employing a variational automatic encoder, and optimizing the data quality; multiple artificial intelligence models are constructed for prediction, so that prediction errors are reduced; according to the method, prediction results of the three models are superposed, fle</description><subject>CALCULATING</subject><subject>CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTINGELECTRIC POWER</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>CONVERSION OR DISTRIBUTION OF ELECTRIC POWER</subject><subject>COUNTING</subject><subject>DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES</subject><subject>ELECTRIC DIGITAL DATA PROCESSING</subject><subject>ELECTRICITY</subject><subject>GENERATION</subject><subject>PHYSICS</subject><subject>SYSTEMS FOR STORING ELECTRIC ENERGY</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>2024</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNyrsKwkAQRuE0FqK-w_gAgjEIWkpQrKzsw7j7JxncS9jZBHx7LbS3OsX55oWpR83RI5EiTWJASfRJmNiNnCUG0pdmePLRwknoyCP30RIH-1sPVlj6UE5ZWjHCjiRkOCcdgsGymLXsFKtvF8X6cr7X1w2G2EAHNgjITX0ry0N53Ffb3an6x7wBCak_Lg</recordid><startdate>20240614</startdate><enddate>20240614</enddate><creator>YU HONGFU</creator><creator>YANG XIAOYAN</creator><creator>SU HONGYU</creator><creator>MO LIANGYUAN</creator><creator>ZHU DI</creator><creator>WANG LICHAO</creator><creator>HUANG KAI</creator><creator>WEI LIUMU</creator><creator>WU CHANGSHAN</creator><creator>LI LIN</creator><creator>FU HUA</creator><creator>ZHU NING</creator><creator>LIU NA</creator><creator>LIAO QIUYUAN</creator><creator>HUANG YUSHAN</creator><scope>EVB</scope></search><sort><creationdate>20240614</creationdate><title>Customer service risk evaluation system modeling method and system based on artificial intelligence</title><author>YU HONGFU ; YANG XIAOYAN ; SU HONGYU ; MO LIANGYUAN ; ZHU DI ; WANG LICHAO ; HUANG KAI ; WEI LIUMU ; WU CHANGSHAN ; LI LIN ; FU HUA ; ZHU NING ; LIU NA ; LIAO QIUYUAN ; HUANG YUSHAN</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN118195302A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2024</creationdate><topic>CALCULATING</topic><topic>CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTINGELECTRIC POWER</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>CONVERSION OR DISTRIBUTION OF ELECTRIC POWER</topic><topic>COUNTING</topic><topic>DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES</topic><topic>ELECTRIC DIGITAL DATA PROCESSING</topic><topic>ELECTRICITY</topic><topic>GENERATION</topic><topic>PHYSICS</topic><topic>SYSTEMS FOR STORING ELECTRIC ENERGY</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>YU HONGFU</creatorcontrib><creatorcontrib>YANG XIAOYAN</creatorcontrib><creatorcontrib>SU HONGYU</creatorcontrib><creatorcontrib>MO LIANGYUAN</creatorcontrib><creatorcontrib>ZHU DI</creatorcontrib><creatorcontrib>WANG LICHAO</creatorcontrib><creatorcontrib>HUANG KAI</creatorcontrib><creatorcontrib>WEI LIUMU</creatorcontrib><creatorcontrib>WU CHANGSHAN</creatorcontrib><creatorcontrib>LI LIN</creatorcontrib><creatorcontrib>FU HUA</creatorcontrib><creatorcontrib>ZHU NING</creatorcontrib><creatorcontrib>LIU NA</creatorcontrib><creatorcontrib>LIAO QIUYUAN</creatorcontrib><creatorcontrib>HUANG YUSHAN</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>YU HONGFU</au><au>YANG XIAOYAN</au><au>SU HONGYU</au><au>MO LIANGYUAN</au><au>ZHU DI</au><au>WANG LICHAO</au><au>HUANG KAI</au><au>WEI LIUMU</au><au>WU CHANGSHAN</au><au>LI LIN</au><au>FU HUA</au><au>ZHU NING</au><au>LIU NA</au><au>LIAO QIUYUAN</au><au>HUANG YUSHAN</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Customer service risk evaluation system modeling method and system based on artificial intelligence</title><date>2024-06-14</date><risdate>2024</risdate><abstract>The invention discloses a customer service risk evaluation system modeling method and system based on artificial intelligence. The method comprises the steps of data collection, data preprocessing, appeal risk evaluation system construction, power failure risk evaluation system construction, load risk evaluation system construction, value added service risk evaluation system construction and customer service risk evaluation system construction. The invention relates to the technical field of power demand customer service risk prediction, in particular to a customer service risk evaluation system modeling method and system based on artificial intelligence, and the method comprises the steps: carrying out the multi-target data generation through employing a variational automatic encoder, and optimizing the data quality; multiple artificial intelligence models are constructed for prediction, so that prediction errors are reduced; according to the method, prediction results of the three models are superposed, fle</abstract><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | |
| ispartof | |
| issn | |
| language | chi ; eng |
| recordid | cdi_epo_espacenet_CN118195302A |
| source | esp@cenet |
| subjects | CALCULATING CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTINGELECTRIC POWER COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING CONVERSION OR DISTRIBUTION OF ELECTRIC POWER COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES ELECTRIC DIGITAL DATA PROCESSING ELECTRICITY GENERATION PHYSICS SYSTEMS FOR STORING ELECTRIC ENERGY SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR |
| title | Customer service risk evaluation system modeling method and system based on artificial intelligence |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-08T12%3A42%3A08IST&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=YU%20HONGFU&rft.date=2024-06-14&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3ECN118195302A%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 |