Electric Load Forecasting in Energy Power Systems Based on Online Gaussian Process Regression Coupled with Multilayer Perceptron Kernel Method-Reference-Cited by-同舟云学术

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Electric Load Forecasting in Energy Power Systems Based on Online Gaussian Process Regression Coupled with Multilayer Perceptron Kernel Method

Published:2022-10-06 Issue: Volume: Page:
ISSN:
Container-title:2022 V International Conference on High Technology for Sustainable Development (HiTech)
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Author:

Guenoupkati Agbassou¹,Salami Adekunlé Akim¹,Tchandao Esso-wazam Honoré²,Ajavon Ayité Sénah Akoda¹

Affiliation:

1. University of Lome,Ecole Nationale Supérieure d'Ingénieurs; E.N.S,I, Centre d'Excellence Régional sur la Maîtrise de I'Elcctricité (CERME),Department of Electrical Engineering,Lome,Togo,1515

2. University of Lome,Ecole Nationale Supérieure d'Ingénieurs; E.N.S,I, Centre d'Excellence Régional sur la Maîtrise de I'Elcctricité (CERME),Lome,Togo,1515

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10145489/10145516/10145558.pdf?arnumber=10145558

Reference23 articles.

1. Gaussian processes for machine learning. 704 MIT Press;rasmussen;Cambridge Mass,2006

2. Global horizontal irradiance forecasting using online sparse Gaussian process regression based on quasiperiodic kernels

3. Short-Term Electricity Load Forecasting Using K-Means Clustering - Artificial Neural Networks Hybrid Model: Case Study Of Benin Electricity Community (CEB)

4. Electrical Load Forecasting Using Artificial Neural Network: The Case Study of the Grid Inter-Connected Network of Benin Electricity Community (CEB)

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