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The Improved Markov Error Correcting Method in Gray SVM for Power Load Forecasting
As the power load forecasting sequence has stochastic growth and nonlinear wave characteristics, grey SVM can effective reflect the growth properties of the sequence and fit the nonlinear relation. Markov chain can easily embody the random characteristic of system by complex factors, so the Markov c...
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| creator | Dongxiao Niu Jialiang Lv Xingzhi Zhang |
| description | As the power load forecasting sequence has stochastic growth and nonlinear wave characteristics, grey SVM can effective reflect the growth properties of the sequence and fit the nonlinear relation. Markov chain can easily embody the random characteristic of system by complex factors, so the Markov chain error correction method was introduce in this paper, the whole forecasting precision of the sequence was optimized, and the transfer matrix for the forecasting sequence was decided, then the accuracy for power load forecasting was greatly improved. Through the demonstration test, the precision is better than ingenuous grey SVM, the method in this paper have feasibility in practice. |
| doi_str_mv | 10.1109/IITA.Workshops.2008.88 |
| format | conference_proceeding |
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Markov chain can easily embody the random characteristic of system by complex factors, so the Markov chain error correction method was introduce in this paper, the whole forecasting precision of the sequence was optimized, and the transfer matrix for the forecasting sequence was decided, then the accuracy for power load forecasting was greatly improved. 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Through the demonstration test, the precision is better than ingenuous grey SVM, the method in this paper have feasibility in practice.</description><subject>Computer errors</subject><subject>Error correction</subject><subject>Information technology</subject><subject>Load forecasting</subject><subject>markov chain</subject><subject>Optimization methods</subject><subject>Power load</subject><subject>Predictive models</subject><subject>Stochastic systems</subject><subject>Support vector machines</subject><subject>SVM algorithm</subject><subject>Technology forecasting</subject><subject>Testing</subject><isbn>0769535054</isbn><isbn>9780769535050</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2008</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotzNFKwzAYBeCADHRzTyBIXqD1T9K0yeUo2yy0KFr1cqTNX1vnlpKWyd7eDuVcHDh8HELuGYSMgX7IsnIVfji_H1rXDyEHUKFSV2QOSaylkCCjGZlfZg1aJeyaLIfhCwCYjhMm5A15KVuk2aH37oSWFsbv3YmuvXeeps57rMfu-EkLHFtnaXekW2_O9PW9oM0knt0Pepo7Y-nGTdYMF31LZo35HnD53wvytlmX6WOQP22zdJUHHQM5BryGiumm0awyfApWtYitUhIaiCU3VicVRlw1lWKaK2uiyqKyDLWMldJCLMjd32-HiLvedwfjz7soERxkLH4BHppSpQ</recordid><startdate>200812</startdate><enddate>200812</enddate><creator>Dongxiao Niu</creator><creator>Jialiang Lv</creator><creator>Xingzhi Zhang</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200812</creationdate><title>The Improved Markov Error Correcting Method in Gray SVM for Power Load Forecasting</title><author>Dongxiao Niu ; Jialiang Lv ; Xingzhi Zhang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i105t-2c0b19ff91ba2a2aebc36d8850f0652ad97be428fb81928da4bde8d1e95688933</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2008</creationdate><topic>Computer errors</topic><topic>Error correction</topic><topic>Information technology</topic><topic>Load forecasting</topic><topic>markov chain</topic><topic>Optimization methods</topic><topic>Power load</topic><topic>Predictive models</topic><topic>Stochastic systems</topic><topic>Support vector machines</topic><topic>SVM algorithm</topic><topic>Technology forecasting</topic><topic>Testing</topic><toplevel>online_resources</toplevel><creatorcontrib>Dongxiao Niu</creatorcontrib><creatorcontrib>Jialiang Lv</creatorcontrib><creatorcontrib>Xingzhi Zhang</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE/IET Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Dongxiao Niu</au><au>Jialiang Lv</au><au>Xingzhi Zhang</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>The Improved Markov Error Correcting Method in Gray SVM for Power Load Forecasting</atitle><btitle>2008 International Symposium on Intelligent Information Technology Application Workshops</btitle><stitle>IITAW</stitle><date>2008-12</date><risdate>2008</risdate><spage>793</spage><epage>796</epage><pages>793-796</pages><isbn>0769535054</isbn><isbn>9780769535050</isbn><abstract>As the power load forecasting sequence has stochastic growth and nonlinear wave characteristics, grey SVM can effective reflect the growth properties of the sequence and fit the nonlinear relation. Markov chain can easily embody the random characteristic of system by complex factors, so the Markov chain error correction method was introduce in this paper, the whole forecasting precision of the sequence was optimized, and the transfer matrix for the forecasting sequence was decided, then the accuracy for power load forecasting was greatly improved. Through the demonstration test, the precision is better than ingenuous grey SVM, the method in this paper have feasibility in practice.</abstract><pub>IEEE</pub><doi>10.1109/IITA.Workshops.2008.88</doi><tpages>4</tpages></addata></record> |
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| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Computer errors Error correction Information technology Load forecasting markov chain Optimization methods Power load Predictive models Stochastic systems Support vector machines SVM algorithm Technology forecasting Testing |
| title | The Improved Markov Error Correcting Method in Gray SVM for Power Load Forecasting |
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