A Computing Model of Artificial Intelligent Approaches to Mid-term Load Forecasting: a state-of-the-art- survey for the researcher-Reference-Cited by-同舟云学术

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A Computing Model of Artificial Intelligent Approaches to Mid-term Load Forecasting: a state-of-the-art- survey for the researcher

Published:2010 Issue:1 Volume:2 Page:94-100
ISSN:1793-8236
Container-title:International Journal of Engineering and Technology
language:
Short-container-title:IJET

Author:

Bunnoon Pituk,Chalermyanont Kusumal,Limsakul Chusak

Publisher

IACSIT Press

Link

http://www.ijetch.org/papers/106-T251.pdf

Cited by 9 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. Electric Energy Demand Forecasting in an Oil Production Company Using Artificial Neural Networks;Lecture Notes in Electrical Engineering;2022

2. A Review of the Conceptualization and Operational Management of Seaport Microgrids on the Shore and Seaside;Energies;2021-11-26

3. Forecasting the load of electrical power systems in mid‐ and long‐term horizons: a review;IET Generation, Transmission & Distribution;2016-12

4. A hybrid dynamic and fuzzy time series model for mid-term power load forecasting;International Journal of Electrical Power & Energy Systems;2015-01

5. Electricity Demand Forecasting;International Journal of Productivity Management and Assessment Technologies;2014-01

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