Long term electric load forecasting based on TS-type recurrent fuzzy neural network model-Reference-Cited by-同舟云学术

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Long term electric load forecasting based on TS-type recurrent fuzzy neural network model

Published:2020-02 Issue: Volume:179 Page:106106
ISSN:0378-7796
Container-title:Electric Power Systems Research
language:en
Short-container-title:Electric Power Systems Research

Author:

Wen Ziteng,Xie Linbo,Fan Qigao,Feng Hongwei

Funder

National Natural Science Foundation

Light Industry Technology and Engineering

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology

Reference33 articles.

1. Benchmarking robustness of load forecasting models under data integrity attacks;Luo;Int. J. Forecasting,2018

2. Holographic ensemble forecasting method for short-term power load;Zhou;IEEE Trans. Smart Grid,2019

3. Long term probabilistic load forecasting and normalization with hourly information;Hong;IEEE Trans. Smart Grid,2014

4. Weather station selection for electric load forecasting;Hong;Int. J. Forecasting,2015

5. A novel multi-time-scale modeling for electric power demand forecasting: from short-term to medium-term horizon;Boroojeni;Electric Power Syst. Res.,2017

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