A Comparative Analysis of Supervised Machine Learning Algorithms for Electricity Demand Forecasting-Reference-Cited by-同舟云学术

A Comparative Analysis of Supervised Machine Learning Algorithms for Electricity Demand Forecasting

Published:2022-03-01 Issue: Volume: Page:
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Container-title:2022 Second International Conference on Power, Control and Computing Technologies (ICPC2T)
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Author:

Rawal Keerti¹,Ahmad Aijaz¹

Affiliation:

1. NIT Srinagar,Department of Electrical Engineering,Srinagar,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9776593/9776643/09776960.pdf?arnumber=9776960

Reference20 articles.

1. On Short-Term Load Forecasting Using Machine Learning Techniques and a Novel Parallel Deep LSTM-CNN Approach

2. Support vector regression based electricity peak load forecasting

3. A comparative study of differ-ent machine learning methods for electricity prices forecasting of an electricity market;foruzan;North American Power Symposium (NAPS) 2015,0

4. Household Energy Prediction: Methods and Applications for Smarter Grid Design

5. Regression Shrinkage and Selection Via the Lasso

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