Uncertainty-Aware Functional Analysis for Electricity Consumption Prediction Using Multi-Task Optimization Learning Model-Reference-Cited by-同舟云学术

Uncertainty-Aware Functional Analysis for Electricity Consumption Prediction Using Multi-Task Optimization Learning Model

Published:2023-10-10 Issue: Volume: Page:
ISSN:
Container-title:2023 International Conference on Computer Science and Emerging Technologies (CSET)
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Author:

Chandrasekaran Saravanan¹,Masthan M.²,R Mahesh T³,Athinarayanan S.⁴,Ram Ashwin⁵,V Vivek³

Affiliation:

1. SRM Institute of Science and Technology, Ramapuram,Department of computer science and Engineering,Chennai,India

2. Arffy Technogies Pvt Ltd.,Bengaluru,Karnataka,India

3. JAIN (Deemed-to-be University),Faculty of Engineering and Technology,Department of Computer Science & Engineering,Bengaluru,India,562112

4. School of Computing Vel Tech Rangarajan Dr. Sagunthala R&D, Institute of Science and Technology, Avadi,Department of CSE,Chennai,Tamil Nadu,India,600062

5. SRM Institute of Science and Technology, Ramapuram,Department of computer science and Engineering (AIML),Chennai,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10346235/10346224/10346821.pdf?arnumber=10346821

Reference21 articles.

1. Short-Term Forecasting for Energy Consumption through Stacking Heterogeneous Ensemble Learning Model

2. A Novel Hybrid Algorithm to Forecast Functional Time Series Based on Pattern Sequence Similarity with Application to Electricity Demand

3. Empirical Mode Decomposition Based Deep Learning for Electricity Demand Forecasting

4. A review of data-driven approaches for prediction and classification of building energy consumption

5. Forecasting the Short-Term Electricity Consumption of Building Using a Novel Ensemble Model

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