The electricity consumption forecast: Adopting a hybrid approach by deep learning and ARIMAX-GARCH models
Author:
Publisher
Elsevier BV
Subject
General Energy
Reference48 articles.
1. An optimized model using LSTM network for demand forecasting;Abbasimehr;Comput. Ind. Eng.,2020
2. Trees vs neurons: Comparison between random forest and ANN for high-resolution prediction of building energy consumption;Ahmad;Energy Build.,2017
3. Short-term wind power forecasting using ridgelet neural network;Amjady;Electr. Power Syst. Res.,2011
4. Generalized autoregressive conditional heteroskedasticity;Bollerslev;J. Econometrics,1986
5. Time Series Analysis: Forecasting and Control, Vol. 734;Box,2011
Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Electrical consumption forecasting in sports venues: A proposed approach based on neural networks and ARIMAX Models;Sustainable Cities and Society;2024-01
2. Data-driven multi-step energy consumption forecasting with complex seasonality patterns and exogenous variables: Model accuracy assessment in change point neighborhoods;Applied Soft Computing;2024-01
3. International oil shocks and the volatility forecasting of Chinese stock market based on machine learning combination models;The North American Journal of Economics and Finance;2024-01
4. Short-term electricity demand forecasting using a hybrid ANFIS–ELM network optimised by an improved parasitism–predation algorithm;Applied Energy;2023-09
5. Wind power forecasting: A hybrid forecasting model and multi-task learning-based framework;Energy;2023-09
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3