A Hybrid Soft Computing Framework for Electrical Energy Optimization

Akhtar, Shamim and Muhamad Zahim, Sujod and Rizvi, Syed Sajjad Hussain (2021) A Hybrid Soft Computing Framework for Electrical Energy Optimization. In: 2021 6th International Multi-Topic ICT Conference (IMTIC) , 10-12 Nov. 2021 , Jamshoro & Karachi, Pakistan. (177765). ISBN 9781665482943

Preview	Pdf A Hybrid Soft Computing Framework for Electrical Energy Optimization partial.pdf Download (532kB) | Preview
	Pdf IEEE_A_Hybrid_Soft_Computing_Framework_for_Electrical_Energy_Optimization.pdf Restricted to Repository staff only Download (526kB) | Request a copy

Abstract

Electricity is a significant and essential player in the modern world economy. It translates into the social, economic, and sectorial growth of any region. The scarcity of these resources demands a highly efficient and robust energy management system (EMS). In the recent literature, many artificial intelligence algorithms have been proposed to cater to the need for efficient and real-time decision-making. Moreover, the hybridization of these algorithms has also been proposed for optimum decision-making. In this paper, a hybrid soft-computing-based framework has been proposed for intelligent energy management and optimization. The proposed model has based on the evolutionary neuro-fuzzy approach that can predict the energy demand as an objective function and optimize the energy within the given constraints. The future extension of this work will be the implementation and validation of the proposed framework on either a real application dataset or dataset opted from the benchmark repository

Item Type:	Conference or Workshop Item (Paper)
Additional Information:	Indexed by Scopus
Uncontrolled Keywords:	component; formatting; insert; style; styling
Subjects:	Q Science > QA Mathematics > QA76 Computer software T Technology > T Technology (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division:	Institute of Postgraduate Studies College of Engineering
Depositing User:	Miss Amelia Binti Hasan
Date Deposited:	08 Sep 2023 03:14
Last Modified:	08 Sep 2023 03:14
URI:	http://umpir.ump.edu.my/id/eprint/38583
Download Statistic:	View Download Statistics

Actions (login required)

View Item