{"title":"用于电力峰值负荷模式发现和时间序列预测的频谱混合核","authors":"T. Ploysuwan","doi":"10.1109/TENCON.2014.7022373","DOIUrl":null,"url":null,"abstract":"In this paper, the author presents the joint of spectral mixture Gaussian and a single squared exponential kernel function which used in predictive solution of Gaussian process (GP) to find new pattern discovery and forecasting of electricity peak load demand of Thailand in next five years. Several analytical results have been evaluated in simulations such as pattern discovery performance, property of each kernel function, and mean absolute percentage error (MAPE) of the method.","PeriodicalId":292057,"journal":{"name":"TENCON 2014 - 2014 IEEE Region 10 Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Spectral mixture kernel for pattern discovery and time series forecasting of electricity peak load\",\"authors\":\"T. Ploysuwan\",\"doi\":\"10.1109/TENCON.2014.7022373\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, the author presents the joint of spectral mixture Gaussian and a single squared exponential kernel function which used in predictive solution of Gaussian process (GP) to find new pattern discovery and forecasting of electricity peak load demand of Thailand in next five years. Several analytical results have been evaluated in simulations such as pattern discovery performance, property of each kernel function, and mean absolute percentage error (MAPE) of the method.\",\"PeriodicalId\":292057,\"journal\":{\"name\":\"TENCON 2014 - 2014 IEEE Region 10 Conference\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"TENCON 2014 - 2014 IEEE Region 10 Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TENCON.2014.7022373\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"TENCON 2014 - 2014 IEEE Region 10 Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TENCON.2014.7022373","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Spectral mixture kernel for pattern discovery and time series forecasting of electricity peak load
In this paper, the author presents the joint of spectral mixture Gaussian and a single squared exponential kernel function which used in predictive solution of Gaussian process (GP) to find new pattern discovery and forecasting of electricity peak load demand of Thailand in next five years. Several analytical results have been evaluated in simulations such as pattern discovery performance, property of each kernel function, and mean absolute percentage error (MAPE) of the method.