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International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering
International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2321-2004ISSN Print 2321-5526Since 2013
IJIREEICE meets the suggestive parameters outlined in the latest University Grants Commission (UGC) for peer-reviewed journals, ensuring high standards of research integrity, publication ethics, and academic excellence.
← Back to VOLUME 8, ISSUE 1, JANUARY 2020

Machine Learning Based Estimation of Power Consumption through Spline Regression

Sunkara Sidhartha, Sucheta Aich Sarkar, Risha Roy, Rachita Brahma, Judhajit Sanyal

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Abstract: Considering the current scenario of steady depletion of primary sources of energy, it is extremely critical to manage the consumption of power. Ensuring low wastage of power involves prediction of power consumption, which can enable generation of power according to the demand. This process is true for both micro-scale estimation and generation, for particular sectors in an urban or rural area, to macro-estimate of power requirements in terms of overall power consumed nationally, that can be further divided into sectors such as commercial and residential power consumption. The present work outlines a machine learning based linear spline regression-based approach to prediction of energy consumption which is an improvement on the standard spline regression based approach employed currently.

Keywords: Power Consumption, Estimation, Machine Learning, Linear Regression, Spline Regression

How to Cite:

[1] Sunkara Sidhartha, Sucheta Aich Sarkar, Risha Roy, Rachita Brahma, Judhajit Sanyal, β€œMachine Learning Based Estimation of Power Consumption through Spline Regression,” International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering (IJIREEICE), DOI: 10.17148/IJIREEICE.2019.8103

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