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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| Format: | Conference or Workshop Item |
| Language: | English English |
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IEEE
2021
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| Online Access: | http://umpir.ump.edu.my/id/eprint/38583/ 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 |
| _version_ | 1848825544057028608 |
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| 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 |
| building | UMP Institutional Repository |
| collection | Online Access |
| 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 |
| first_indexed | 2025-11-15T03:30:36Z |
| format | Conference or Workshop Item |
| id | ump-38583 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-15T03:30:36Z |
| publishDate | 2021 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-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 (Published) https://doi.org/10.1109/IMTIC53841.2021.9719856 |
| 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 |
| title | 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_short | A Hybrid Soft Computing Framework for Electrical Energy Optimization |
| title_sort | hybrid soft computing framework for electrical energy optimization |
| topic | QA76 Computer software T Technology (General) TK Electrical engineering. Electronics Nuclear engineering |
| url | http://umpir.ump.edu.my/id/eprint/38583/ http://umpir.ump.edu.my/id/eprint/38583/ 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 |