Forecasting of Energy Consumption in the Philippines Using Machine Learning Algorithms-Reference-Cited by-同舟云学术

Forecasting of Energy Consumption in the Philippines Using Machine Learning Algorithms

Published:2023 Issue: Volume: Page:424-435
ISSN:1865-0929
Container-title:Recent Challenges in Intelligent Information and Database Systems
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Author:

Torculas Erru,Rentillo Earl James,Ambita Ara Abigail

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-42430-4_35

Reference15 articles.

1. Barak, S., Sadegh, S.: Forecasting energy consumption using ensemble ARIMA-ANFIS hybrid algorithm. Int. J. Electr. Power Energy Syst. 82, 92–104 (2016)

2. The National Institute of Open Schooling (NIOS). Importance of Energy in the Society (2012). https://nios.ac.in/media/documents/333courseE/27B.pdf. Accessed 27 Nov 2022

3. Ritchie, H., Roser, M., Rosado, P.: Philippines: energy country profile. Our World in Data (2022). https://ourworldindata.org/energy/country/philippines. Accessed 27 Nov 2022

4. Sahakian, M.D.: Understanding household energy consumption patterns: when “west is best. Metro Manila”. Energy Policy 39(2), 596–602 (2011)

5. Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence);E García-Martín,2019

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