Shining a Light on Solar Power Forecasting: Machine Learning Techniques for Unprecedented Accuracy
Author:
Affiliation:
1. Chandigarh University,Department of CSE,Mohali,Punjab,India
2. Krishna Institute of Medical Sciences,Department of Psychiatry,Karad,Maharashtra,India
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10389811/10389819/10390265.pdf?arnumber=10390265
Reference19 articles.
1. Exploring the Effectiveness of Optimized Convolutional Neural Network in Transfer Learning for Image Classification: A Practical Approach
2. Forecasting Day-Ahead Solar Radiation Using Machine Learning Approach
3. Predicting solar generation from weather forecasts using machine learning
4. IoT-based ECG monitoring for arrhythmia classification using Coyote Grey Wolf optimization-based deep learning CNN classifier
5. Solar Power Forecasting Using Support Vector Regression;Abuella;arXiv,2017
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1. Evaluating Solar Power Forecasting Robustness: A Comparative Analysis of XGBoost, RNN, KNN, RF, and LSTM with emphasis on Lagged Steps, Sensitivity, and Cross-Validation Techniques;2024 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE);2024-08-06
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