Application of time-series and Artificial Neural Network models in short term load forecasting for scheduling of storage devices-Reference-Cited by-同舟云学术

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Application of time-series and Artificial Neural Network models in short term load forecasting for scheduling of storage devices

Published:2014-09 Issue: Volume: Page:
ISSN:
Container-title:2014 49th International Universities Power Engineering Conference (UPEC)
language:
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Author:

Ahmed K. M. U.,Ampatzis M.,Nguyen P. H.,Kling W. L.

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/6917609/6934581/06934761.pdf?arnumber=6934761

Cited by 7 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 Load Forecasting of Electricity Demand for the Residential Sector Based on Modelling Techniques: A Systematic Review;Energies;2023-05-15

2. Electricity Load Combination Prediction Based on Fuzzy Clustering;2023 6th International Conference on Energy, Electrical and Power Engineering (CEEPE);2023-05-12

3. Comparison of Machine Learning Models for Week-Ahead Load Forecasting in Short-term Power System Planning;2022 North American Power Symposium (NAPS);2022-10-09

4. Short-Dataset-Driven Prediction on Area Electricity Consumption with Adaptive Training Window Selection;2022 IEEE International Conferences on Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, Physical & Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics);2022-08

5. Prediction of Photovoltaic Panel Power Outputs using Time Series and Artificial Neural Network Methods;Tekirdağ Ziraat Fakültesi Dergisi;2021-03-29

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