负荷大数据时间序列分析模型预测比较研究

Proceedings of the International Conference on Research in Adaptive and Convergent Systems Pub Date : 2017-09-20 DOI:10.1145/3129676.3129719

Jaehyung Kim, Taehyoung Kim, K. Ham

{"title":"负荷大数据时间序列分析模型预测比较研究","authors":"Jaehyung Kim, Taehyoung Kim, K. Ham","doi":"10.1145/3129676.3129719","DOIUrl":null,"url":null,"abstract":"As energy supply changes become more important, interest in the field of efficient energy management is increasing. In this paper, demand forecasting is performed through time series analysis of power big data. And we measured the performance through predictive comparison of time series prediction model.","PeriodicalId":326100,"journal":{"name":"Proceedings of the International Conference on Research in Adaptive and Convergent Systems","volume":"108 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Study on Prediction Comparison by Time Series Analysis Model of Load Big data\",\"authors\":\"Jaehyung Kim, Taehyoung Kim, K. Ham\",\"doi\":\"10.1145/3129676.3129719\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As energy supply changes become more important, interest in the field of efficient energy management is increasing. In this paper, demand forecasting is performed through time series analysis of power big data. And we measured the performance through predictive comparison of time series prediction model.\",\"PeriodicalId\":326100,\"journal\":{\"name\":\"Proceedings of the International Conference on Research in Adaptive and Convergent Systems\",\"volume\":\"108 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-09-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the International Conference on Research in Adaptive and Convergent Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3129676.3129719\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the International Conference on Research in Adaptive and Convergent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3129676.3129719","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

摘要

随着能源供应的变化变得越来越重要，人们对高效能源管理领域的兴趣日益增加。本文通过电力大数据的时间序列分析进行需求预测。并通过时间序列预测模型的预测比较来衡量其性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

A Study on Prediction Comparison by Time Series Analysis Model of Load Big data

As energy supply changes become more important, interest in the field of efficient energy management is increasing. In this paper, demand forecasting is performed through time series analysis of power big data. And we measured the performance through predictive comparison of time series prediction model.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Proceedings of the International Conference on Research in Adaptive and Convergent Systems

自引率

0.00%

发文量