journal-of-statistics-and-management-systems Journal of Statistics and Management Systems 2169-0014 0972-0510 Taru Publications 10.47974/JSMS-1316 Interdisciplinary role of statistics in energy consumption prediction within smart grid big data analytics Sharma Kamal Muma College of Business, 8350 N. Tamiami Trail Sarasota, University of South Florida, Florida, FL 34243, U.S.A. Department of Mechanical Engineering, GLA University, Mathura, Uttar Pradesh, 281406, India Unhelkar Bhuvan Muma College of Business, 8350 N. Tamiami Trail Sarasota, University of South Florida, Florida, FL 34243, U.S.A. Shankar S. Siva Department of Computer Science and Engineering, KG Reddy College of Engineering and Technology, Moinabad, Telangana, 500075, India Chakrabarti Tulika Department of Chemistry, Sir Padampat Singhania University, Udaipur, Rajasthan, 313601, India Chakrabarti Prasun Department of Computer Science and Engineering, Sir Padampat Singhania University, Udaipur, Rajasthan, 313601, India Sivaneasan B. Specialist Adult Educator Engineering, Electrical Power Engineering Programme, 1 Punggol Coast Road, Singapore Institute of Technology, 828608, Singapore Margala Martin School of Computing and Informatics, University of Louisiana, Lafayette, LA 70503, U.S.A. 28 1 95 105 15 01 2025

The study of energy consumption in buildings is crucial due to environmental and financial impacts. Smart metering is suggested to improve energy efficiency, but predicting electrical consumption accurately remains challenging, considering various factors. To tackle this, we propose a Multi-objective Golden Eagle Optimization (MGE) based Hybrid Deep Dynamic Convolutional Fuzzy Network (HDDCFN) method. This approach optimizes algorithm parameters and prediction models using multi-objective optimization, considering historical usage and weather conditions. The research is conducted using Matlab.

 Energy time series Energy prediction Interdisciplinary Smart meters Smart grid (SG) Energy time series Optimization and artificial intelligence access open retracted no