Prediction model training method based on big data and photovoltaic power generation performance detection method
The embodiment of the invention discloses a prediction model training method based on big data and a photovoltaic power generation performance detection method. The training method comprises the following steps: carrying out model training on an LSTM common model based on a first training set, respe...
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creator | GUO JIANBO ZHANG LEI JIN ZHIBIN LU LINGLING ZHANG WEI ZHANG QIANG HE JIE TAO YONGJING |
description | The embodiment of the invention discloses a prediction model training method based on big data and a photovoltaic power generation performance detection method. The training method comprises the following steps: carrying out model training on an LSTM common model based on a first training set, respectively training a plurality of LSTM independent models based on a plurality of second training sets, and judging, screening and determining an optimal model as a photovoltaic power generation power prediction model by utilizing a first loss function; and then, performing hyper-parameter training on the photovoltaic power generation power prediction model based on the test set, and performing prediction judgment by using a second loss function to obtain a photovoltaic power generation power prediction model with an optimal hyper-parameter. According to the detection method, power generation power prediction detection is carried out based on a photovoltaic power generation power prediction model obtained through tra |
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The training method comprises the following steps: carrying out model training on an LSTM common model based on a first training set, respectively training a plurality of LSTM independent models based on a plurality of second training sets, and judging, screening and determining an optimal model as a photovoltaic power generation power prediction model by utilizing a first loss function; and then, performing hyper-parameter training on the photovoltaic power generation power prediction model based on the test set, and performing prediction judgment by using a second loss function to obtain a photovoltaic power generation power prediction model with an optimal hyper-parameter. According to the detection method, power generation power prediction detection is carried out based on a photovoltaic power generation power prediction model obtained through tra</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER ; COUNTING ; ELECTRIC DIGITAL DATA PROCESSING ; ELECTRICITY ; GENERATION ; GENERATION OF ELECTRIC POWER BY CONVERSION OF INFRA-REDRADIATION, VISIBLE LIGHT OR ULTRAVIOLET LIGHT, E.G. 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The training method comprises the following steps: carrying out model training on an LSTM common model based on a first training set, respectively training a plurality of LSTM independent models based on a plurality of second training sets, and judging, screening and determining an optimal model as a photovoltaic power generation power prediction model by utilizing a first loss function; and then, performing hyper-parameter training on the photovoltaic power generation power prediction model based on the test set, and performing prediction judgment by using a second loss function to obtain a photovoltaic power generation power prediction model with an optimal hyper-parameter. According to the detection method, power generation power prediction detection is carried out based on a photovoltaic power generation power prediction model obtained through tra</description><subject>CALCULATING</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>ELECTRIC DIGITAL DATA PROCESSING</subject><subject>ELECTRICITY</subject><subject>GENERATION</subject><subject>GENERATION OF ELECTRIC POWER BY CONVERSION OF INFRA-REDRADIATION, VISIBLE LIGHT OR ULTRAVIOLET LIGHT, E.G. USINGPHOTOVOLTAIC [PV] MODULES</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2023</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNzDEOgkAQhWEaC6PeYTyAxUoitSEYK2NhT4bdB2wCO-sy0etLCAewesX_8m2z9zPBeateAo3iMJAm9sGHjkZoL44anuBozo3vyLEycXAUe1H5yKDsLUX5IlGHgMSLFJFaSSMHC3JQrP4C7rNNy8OEw7q77HirXuX9hCg1psh2drQuH8YUxuTnS3HN__n8ANdxRDM</recordid><startdate>20231124</startdate><enddate>20231124</enddate><creator>GUO JIANBO</creator><creator>ZHANG LEI</creator><creator>JIN ZHIBIN</creator><creator>LU LINGLING</creator><creator>ZHANG WEI</creator><creator>ZHANG QIANG</creator><creator>HE JIE</creator><creator>TAO YONGJING</creator><scope>EVB</scope></search><sort><creationdate>20231124</creationdate><title>Prediction model training method based on big data and photovoltaic power generation performance detection method</title><author>GUO JIANBO ; ZHANG LEI ; JIN ZHIBIN ; LU LINGLING ; ZHANG WEI ; ZHANG QIANG ; HE JIE ; TAO YONGJING</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN117113267A3</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>CONVERSION OR DISTRIBUTION OF ELECTRIC POWER</topic><topic>COUNTING</topic><topic>ELECTRIC DIGITAL DATA PROCESSING</topic><topic>ELECTRICITY</topic><topic>GENERATION</topic><topic>GENERATION OF ELECTRIC POWER BY CONVERSION OF INFRA-REDRADIATION, VISIBLE LIGHT OR ULTRAVIOLET LIGHT, E.G. USINGPHOTOVOLTAIC [PV] MODULES</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>GUO JIANBO</creatorcontrib><creatorcontrib>ZHANG LEI</creatorcontrib><creatorcontrib>JIN ZHIBIN</creatorcontrib><creatorcontrib>LU LINGLING</creatorcontrib><creatorcontrib>ZHANG WEI</creatorcontrib><creatorcontrib>ZHANG QIANG</creatorcontrib><creatorcontrib>HE JIE</creatorcontrib><creatorcontrib>TAO YONGJING</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>GUO JIANBO</au><au>ZHANG LEI</au><au>JIN ZHIBIN</au><au>LU LINGLING</au><au>ZHANG WEI</au><au>ZHANG QIANG</au><au>HE JIE</au><au>TAO YONGJING</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Prediction model training method based on big data and photovoltaic power generation performance detection method</title><date>2023-11-24</date><risdate>2023</risdate><abstract>The embodiment of the invention discloses a prediction model training method based on big data and a photovoltaic power generation performance detection method. The training method comprises the following steps: carrying out model training on an LSTM common model based on a first training set, respectively training a plurality of LSTM independent models based on a plurality of second training sets, and judging, screening and determining an optimal model as a photovoltaic power generation power prediction model by utilizing a first loss function; and then, performing hyper-parameter training on the photovoltaic power generation power prediction model based on the test set, and performing prediction judgment by using a second loss function to obtain a photovoltaic power generation power prediction model with an optimal hyper-parameter. According to the detection method, power generation power prediction detection is carried out based on a photovoltaic power generation power prediction model obtained through tra</abstract><oa>free_for_read</oa></addata></record> |
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subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING CONVERSION OR DISTRIBUTION OF ELECTRIC POWER COUNTING ELECTRIC DIGITAL DATA PROCESSING ELECTRICITY GENERATION GENERATION OF ELECTRIC POWER BY CONVERSION OF INFRA-REDRADIATION, VISIBLE LIGHT OR ULTRAVIOLET LIGHT, E.G. USINGPHOTOVOLTAIC [PV] MODULES PHYSICS |
title | Prediction model training method based on big data and photovoltaic power generation performance detection method |
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