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A Hybrid Soft Computing Framework for Electrical Energy Optimization

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...

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Main Authors: Akhtar, Shamim, Muhamad Zahim, Sujod, Rizvi, Syed Sajjad Hussain
Format: Conference or Workshop Item
Language:English
English
Published: IEEE 2021
Subjects:
QA76 Computer software
T Technology (General)
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://umpir.ump.edu.my/id/eprint/38583/1/A%20Hybrid%20Soft%20Computing%20Framework%20for%20Electrical%20Energy%20Optimization%20partial.pdf
http://umpir.ump.edu.my/id/eprint/38583/2/IEEE_A_Hybrid_Soft_Computing_Framework_for_Electrical_Energy_Optimization.pdf
http://umpir.ump.edu.my/id/eprint/38583/
https://doi.org/10.1109/IMTIC53841.2021.9719856
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spelling my.ump.umpir.385832023-09-08T03:14:00Z http://umpir.ump.edu.my/id/eprint/38583/ A Hybrid Soft Computing Framework for Electrical Energy Optimization Akhtar, Shamim Muhamad Zahim, Sujod Rizvi, Syed Sajjad Hussain QA76 Computer software T Technology (General) TK Electrical engineering. Electronics Nuclear engineering 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 IEEE 2021 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/38583/1/A%20Hybrid%20Soft%20Computing%20Framework%20for%20Electrical%20Energy%20Optimization%20partial.pdf pdf en http://umpir.ump.edu.my/id/eprint/38583/2/IEEE_A_Hybrid_Soft_Computing_Framework_for_Electrical_Energy_Optimization.pdf 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 https://doi.org/10.1109/IMTIC53841.2021.9719856
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
English
topic QA76 Computer software
T Technology (General)
TK Electrical engineering. Electronics Nuclear engineering
spellingShingle QA76 Computer software
T Technology (General)
TK Electrical engineering. Electronics Nuclear engineering
Akhtar, Shamim
Muhamad Zahim, Sujod
Rizvi, Syed Sajjad Hussain
A Hybrid Soft Computing Framework for Electrical Energy Optimization
description 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
format Conference or Workshop Item
author Akhtar, Shamim
Muhamad Zahim, Sujod
Rizvi, Syed Sajjad Hussain
author_facet Akhtar, Shamim
Muhamad Zahim, Sujod
Rizvi, Syed Sajjad Hussain
author_sort Akhtar, Shamim
title A Hybrid Soft Computing Framework for Electrical Energy Optimization
title_short A Hybrid Soft Computing Framework for Electrical Energy Optimization
title_full A Hybrid Soft Computing Framework for Electrical Energy Optimization
title_fullStr A Hybrid Soft Computing Framework for Electrical Energy Optimization
title_full_unstemmed A Hybrid Soft Computing Framework for Electrical Energy Optimization
title_sort hybrid soft computing framework for electrical energy optimization
publisher IEEE
publishDate 2021
url http://umpir.ump.edu.my/id/eprint/38583/1/A%20Hybrid%20Soft%20Computing%20Framework%20for%20Electrical%20Energy%20Optimization%20partial.pdf
http://umpir.ump.edu.my/id/eprint/38583/2/IEEE_A_Hybrid_Soft_Computing_Framework_for_Electrical_Energy_Optimization.pdf
http://umpir.ump.edu.my/id/eprint/38583/
https://doi.org/10.1109/IMTIC53841.2021.9719856
_version_ 1778161089404469248
score 13.211869

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