A Short-Term Load Forecasting Scheme Based on Auto-Encoder and Random Forest
Author:
Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-030-21507-1_21
Reference9 articles.
1. Lahouar, A., Slama, J.B.H.: Day-ahead load forecast using random forest and expert input selection. Energy Convers. Manage. 130, 1040–1051 (2015)
2. Moon, J., Kim, K.-H., Kim, Y., Hwang, E.: A short-term electric load forecasting scheme using 2-stage predictive analytics. In: 5th IEEE International Conference on Big Data and Smart Computing, pp. 219–226. IEEE Press, Shanghai (2018)
3. Bagnasco, A., Fresi, F., Saviozzi, M., Silvestro, F., Vinci, A.: Electrical consumption forecasting in hospital facilities: an application case. Energy Build. 103, 261–270 (2015)
4. Palchak, D., Suryanarayanan, S., Zimmerle, D.: An artificial neural network in short-term electrical load forecasting of a university campus: a case study. J. Energy Resour. Technol. 135(3), 032001 (2013)
5. Moon, J., Park, J., Hwang, E., Jun, S.: Forecasting power consumption for higher educational institutions based on machine learning. J. Supercomput. 74(8), 1–23 (2018)
Cited by 13 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. A Hybrid Ensemble Model for Solar Irradiance Forecasting: Advancing Digital Models for Smart Island Realization;Electronics;2023-06-09
2. Comparative Analysis of Machine Learning Models for Short-Term Load Forecasting;2022 OPJU International Technology Conference on Emerging Technologies for Sustainable Development (OTCON);2023-02-08
3. Models of Load Forecasting;Lecture Notes in Electrical Engineering;2023
4. Deep Learning Techniques for Load Forecasting;Lecture Notes in Electrical Engineering;2023
5. Adaptive Load Forecasting Methodology Based on Generalized Additive Model with Automatic Variable Selection;Sensors;2022-09-24
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