ANN-Enhanced Energy Reference Models for Industrial Buildings: Multinational Company Case Study
This paper established a novel approach for developing simplified yet accurate models using artificial neural networks (ANNs) in industrial environments. It demonstrates that combining nonlinear regression with neural network modeling enhances predictive accuracy while maintaining the inherent simpl...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Wiley
2024-01-01
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| Series: | Modelling and Simulation in Engineering |
| Online Access: | http://dx.doi.org/10.1155/2024/1179795 |
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| _version_ | 1832544787536805888 |
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| author | Younes Ouaomar Said Benkechcha Mourad Kaddiri |
| author_facet | Younes Ouaomar Said Benkechcha Mourad Kaddiri |
| author_sort | Younes Ouaomar |
| collection | DOAJ |
| description | This paper established a novel approach for developing simplified yet accurate models using artificial neural networks (ANNs) in industrial environments. It demonstrates that combining nonlinear regression with neural network modeling enhances predictive accuracy while maintaining the inherent simplicity of ANNs. Industrial sectors are increasingly adopting environmentally friendly practices, driven by the recognition that sustainable initiatives can lead to significant and lasting financial benefits rather than merely a sense of ecological duty. Integrating energy efficiency practices offers potential advantages in waste reduction and resource conservation, which can decrease operating expenses over time. This contributes significantly to pollution mitigation by reducing overall energy consumption cost-effectively. Numerical simulations based on experimental results validate the proposed method, addressing the complexity and accuracy challenges in business models within the energy sector. |
| format | Article |
| id | doaj-art-df3680f916e64a9c85f8ddd04ea8530c |
| institution | Kabale University |
| issn | 1687-5605 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Modelling and Simulation in Engineering |
| spelling | doaj-art-df3680f916e64a9c85f8ddd04ea8530c2025-02-03T09:55:36ZengWileyModelling and Simulation in Engineering1687-56052024-01-01202410.1155/2024/1179795ANN-Enhanced Energy Reference Models for Industrial Buildings: Multinational Company Case StudyYounes Ouaomar0Said Benkechcha1Mourad Kaddiri2Industrial Engineering and Surface Engineering LaboratoryIndustrial Engineering and Surface Engineering LaboratoryIndustrial Engineering and Surface Engineering LaboratoryThis paper established a novel approach for developing simplified yet accurate models using artificial neural networks (ANNs) in industrial environments. It demonstrates that combining nonlinear regression with neural network modeling enhances predictive accuracy while maintaining the inherent simplicity of ANNs. Industrial sectors are increasingly adopting environmentally friendly practices, driven by the recognition that sustainable initiatives can lead to significant and lasting financial benefits rather than merely a sense of ecological duty. Integrating energy efficiency practices offers potential advantages in waste reduction and resource conservation, which can decrease operating expenses over time. This contributes significantly to pollution mitigation by reducing overall energy consumption cost-effectively. Numerical simulations based on experimental results validate the proposed method, addressing the complexity and accuracy challenges in business models within the energy sector.http://dx.doi.org/10.1155/2024/1179795 |
| spellingShingle | Younes Ouaomar Said Benkechcha Mourad Kaddiri ANN-Enhanced Energy Reference Models for Industrial Buildings: Multinational Company Case Study Modelling and Simulation in Engineering |
| title | ANN-Enhanced Energy Reference Models for Industrial Buildings: Multinational Company Case Study |
| title_full | ANN-Enhanced Energy Reference Models for Industrial Buildings: Multinational Company Case Study |
| title_fullStr | ANN-Enhanced Energy Reference Models for Industrial Buildings: Multinational Company Case Study |
| title_full_unstemmed | ANN-Enhanced Energy Reference Models for Industrial Buildings: Multinational Company Case Study |
| title_short | ANN-Enhanced Energy Reference Models for Industrial Buildings: Multinational Company Case Study |
| title_sort | ann enhanced energy reference models for industrial buildings multinational company case study |
| url | http://dx.doi.org/10.1155/2024/1179795 |
| work_keys_str_mv | AT younesouaomar annenhancedenergyreferencemodelsforindustrialbuildingsmultinationalcompanycasestudy AT saidbenkechcha annenhancedenergyreferencemodelsforindustrialbuildingsmultinationalcompanycasestudy AT mouradkaddiri annenhancedenergyreferencemodelsforindustrialbuildingsmultinationalcompanycasestudy |