Investigating the Impact of Data Normalization Methods on Predicting Electricity Consumption in a Building Using different Artificial Neural Network Models.
Author:
Publisher
Elsevier BV
Reference86 articles.
1. A Review on Deep Learning with Focus on Deep Recurrent Neural Network for Electricity Forecasting in Residential Building;Abdulrahman;Procedia Computer Science,2021
2. CNN-LSTM: An efficient hybrid deep learning architecture for predicting short-term photovoltaic power production;Agga;Electric Power Systems Research,2022
3. Deep learning for multi-scale smart energy forecasting;Ahmad;Energy,2019
4. Investigating the Impact of Min-Max Data Normalization on the Regression Performance of K-Nearest Neighbor with Different Similarity Measurements;Ali;Aro-the Scientific Journal of Koya University,2022
5. Normalization of mean squared differences to measure agreement for continuous data;Almehrizi;Statistical Methods in Medical Research,2016
Cited by 1 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. Short-Term Wind Power Prediction Based on Multi-Feature Domain Learning;Energies;2024-07-05
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