A fuzzy adaptive symbiotic organism search based hybrid wavelet transform-extreme learning machine model for load forecasting of power system: a case study-Reference-Cited by-同舟云学术

A fuzzy adaptive symbiotic organism search based hybrid wavelet transform-extreme learning machine model for load forecasting of power system: a case study

Published:2022-08-09 Issue: Volume: Page:
ISSN:1868-5137
Container-title:Journal of Ambient Intelligence and Humanized Computing
language:en
Short-container-title:J Ambient Intell Human Comput

Author:

Nayak Jyoti Ranjan^ORCID,Shaw Binod,Sahu Binod Kumar

Publisher

Springer Science and Business Media LLC

Subject

General Computer Science

Link

https://link.springer.com/content/pdf/10.1007/s12652-022-04355-1.pdf

Reference40 articles.

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3. Barman M, Choudhury NBD, Sutradhar S (2018) A regional hybrid GOA-SVM model based on similar day approach for short-term load forecasting in Assam, India. Energy 145:710–720. https://doi.org/10.1016/j.energy.2017.12.156

4. Chen J, Wang W, Huang C (1995) Analysis of an adaptive time-series autoregressive moving-average (ARMA) model for short-term load forecasting. Electr Power Syst Res 34:187–196

5. Cheng MY, Prayogo D (2014) Symbiotic Organisms Search: a new metaheuristic optimization algorithm. Comput Struct 139:98–112. https://doi.org/10.1016/j.compstruc.2014.03.007

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