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Temperatures data preprocessing for short-term gas consumption forecast
Final quality of every prediction model is significantly dependent on the quality and good preprocessing of its input data. A case-based reasoning method is presented for outside temperature data preprocessing for the purpose of short-term gas consumption forecasting. The great advantage of our appr...
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creator | Simunek, M. Pelikan, E. |
description | Final quality of every prediction model is significantly dependent on the quality and good preprocessing of its input data. A case-based reasoning method is presented for outside temperature data preprocessing for the purpose of short-term gas consumption forecasting. The great advantage of our approach is its simplicity, stability and predictability of results. The suggested method is used both for handling missing data and for user input preprocessing when hourly temperatures profile is computed from few input values. The presented algorithm is computationally robust and is implemented in several real-time systems. |
doi_str_mv | 10.1109/ISIE.2008.4676945 |
format | conference_proceeding |
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A case-based reasoning method is presented for outside temperature data preprocessing for the purpose of short-term gas consumption forecasting. The great advantage of our approach is its simplicity, stability and predictability of results. The suggested method is used both for handling missing data and for user input preprocessing when hourly temperatures profile is computed from few input values. The presented algorithm is computationally robust and is implemented in several real-time systems.</description><identifier>ISSN: 2163-5137</identifier><identifier>ISBN: 1424416655</identifier><identifier>ISBN: 9781424416653</identifier><identifier>EISBN: 1424416663</identifier><identifier>EISBN: 9781424416660</identifier><identifier>DOI: 10.1109/ISIE.2008.4676945</identifier><identifier>LCCN: 2007936380</identifier><language>eng</language><publisher>IEEE</publisher><subject>Computer science ; Data preprocessing ; Economic forecasting ; Predictive models ; Real time systems ; Robustness ; Stability ; Temperature dependence ; Temperature measurement ; Weather forecasting</subject><ispartof>2008 IEEE International Symposium on Industrial Electronics, 2008, p.1192-1196</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/4676945$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/4676945$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Simunek, M.</creatorcontrib><creatorcontrib>Pelikan, E.</creatorcontrib><title>Temperatures data preprocessing for short-term gas consumption forecast</title><title>2008 IEEE International Symposium on Industrial Electronics</title><addtitle>ISIE</addtitle><description>Final quality of every prediction model is significantly dependent on the quality and good preprocessing of its input data. A case-based reasoning method is presented for outside temperature data preprocessing for the purpose of short-term gas consumption forecasting. The great advantage of our approach is its simplicity, stability and predictability of results. The suggested method is used both for handling missing data and for user input preprocessing when hourly temperatures profile is computed from few input values. The presented algorithm is computationally robust and is implemented in several real-time systems.</description><subject>Computer science</subject><subject>Data preprocessing</subject><subject>Economic forecasting</subject><subject>Predictive models</subject><subject>Real time systems</subject><subject>Robustness</subject><subject>Stability</subject><subject>Temperature dependence</subject><subject>Temperature measurement</subject><subject>Weather forecasting</subject><issn>2163-5137</issn><isbn>1424416655</isbn><isbn>9781424416653</isbn><isbn>1424416663</isbn><isbn>9781424416660</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2008</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNpFkM1Kw0AUhUe0YFv7AOImL5B45-9mspRSa6DgwuzLZOamBswPM9OFb2_FgqvD4XznLA5jjxwKzqF6rj_qXSEATKGwxErpG7biSijFEVHe_hut79hScJS55rJcsNWlVFYSpYF7tomxb4EDluqCLNm-oWGmYNM5UMy8TTabA81hcnQhx1PWTSGLn1NIeaIwZCcbMzeN8TzMqZ_G35icjemBLTr7FWlz1TVrXnfN9i0_vO_r7csh7ytIORki7lCR0KWrHC9F51G1AF4ieG9bTui8UG3VGQO-bclxrY1BYcCB7eSaPf3N9kR0nEM_2PB9vB4ifwDRXlIF</recordid><startdate>200806</startdate><enddate>200806</enddate><creator>Simunek, M.</creator><creator>Pelikan, E.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200806</creationdate><title>Temperatures data preprocessing for short-term gas consumption forecast</title><author>Simunek, M. ; Pelikan, E.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-e8ee1c64e257c9c172fd64b00d360ddab1e6cd24b9f880dbbec155886280c0af3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2008</creationdate><topic>Computer science</topic><topic>Data preprocessing</topic><topic>Economic forecasting</topic><topic>Predictive models</topic><topic>Real time systems</topic><topic>Robustness</topic><topic>Stability</topic><topic>Temperature dependence</topic><topic>Temperature measurement</topic><topic>Weather forecasting</topic><toplevel>online_resources</toplevel><creatorcontrib>Simunek, M.</creatorcontrib><creatorcontrib>Pelikan, E.</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</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>Simunek, M.</au><au>Pelikan, E.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Temperatures data preprocessing for short-term gas consumption forecast</atitle><btitle>2008 IEEE International Symposium on Industrial Electronics</btitle><stitle>ISIE</stitle><date>2008-06</date><risdate>2008</risdate><spage>1192</spage><epage>1196</epage><pages>1192-1196</pages><issn>2163-5137</issn><isbn>1424416655</isbn><isbn>9781424416653</isbn><eisbn>1424416663</eisbn><eisbn>9781424416660</eisbn><abstract>Final quality of every prediction model is significantly dependent on the quality and good preprocessing of its input data. A case-based reasoning method is presented for outside temperature data preprocessing for the purpose of short-term gas consumption forecasting. The great advantage of our approach is its simplicity, stability and predictability of results. The suggested method is used both for handling missing data and for user input preprocessing when hourly temperatures profile is computed from few input values. The presented algorithm is computationally robust and is implemented in several real-time systems.</abstract><pub>IEEE</pub><doi>10.1109/ISIE.2008.4676945</doi><tpages>5</tpages></addata></record> |
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ispartof | 2008 IEEE International Symposium on Industrial Electronics, 2008, p.1192-1196 |
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source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Computer science Data preprocessing Economic forecasting Predictive models Real time systems Robustness Stability Temperature dependence Temperature measurement Weather forecasting |
title | Temperatures data preprocessing for short-term gas consumption forecast |
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