Prediction of Hourly Cooling Energy Consumption of Educational Buildings Using Artificial Neural Network
How to cite (IJASEIT) :
D. A. Asimakopoulos, M. Santamouris, I. Farrou, M. Laskari, M. Saliari, G. Zanis, G. Giannakidis, K. Tigas, J. Kapsomenakis, C. Douvis, S. C. Zerefos, T. Antonakaki, and C. Giannakopoulos, "Modelling the energy demand projection of the building sector in Greece in the 21st century," Energy and Buildings, vol. 49, pp. 488-498, 2012/06/01/ 2012.
L. Pí©rez-Lombard, J. Ortiz, and C. Pout, "A review on buildings energy consumption information," Energy and Buildings, vol. 40, pp. 394-398, 2008/01/01/ 2008.
S. Javeed Nizami and A. Z. Al-Garni, "Forecasting electric energy consumption using neural networks," Energy Policy, vol. 23, pp. 1097-1104, 1995/12/01/ 1995.
S. A. Kalogirou, C. C. Neocleous, and C. N. Schizas, "BUILDING HEATING LOAD ESTIMATION USING ARTIFICIAL NEURAL NETWORKS," presented at the Proceedings of Clima 2000 Conference, Brussels, 1997.
F. D. M. Chaves, "Artificial neural networks for electricity consumption forecasting considering climatic factors," in Proc of the 11th WSEAS Int Conf on Neural Networks, NN '10, Proceedings of the 11th WSEAS Int Conf on Evolutionary Computing, EC '10, Proc of the 11th WSEAS Int Conf on Fuzzy Systems, FS '10, 2010, pp. 293-298.
W. Mai, C. Y. Chung, T. Wu, and H. Huang, "Electric load forecasting for large office building based on radial basis function neural network," in IEEE Power and Energy Society General Meeting, 2014.
M. W. Ahmad, M. Mourshed, and Y. Rezgui, "Trees vs Neurons: Comparison between Random Forest and ANN for high-resolution prediction of building energy consumption," Energy and Buildings, vol. 147, 2017.
C. Deb, S. E. Lee, and M. Santamouris, "Using artificial neural networks to assess HVAC related energy saving in retrofitted office buildings," Solar Energy, vol. 163, pp. 32-44, 2018/03/15/ 2018.
M. Kharseh and M. Al-Khawaja, "Retrofitting measures for reducing buildings cooling requirements in cooling-dominated environment: Residential house," Applied Thermal Engineering, vol. 98, pp. 352-356, 2016/04/05/ 2016.
H. H. Sait, "Estimated Thermal Load and Selecting of Suitable Air-conditioning Systems for a Three Story Educational Building," Procedia Computer Science, vol. 19, pp. 636-645, 2013/01/01/ 2013.
K. Li, X. Xie, W. Xue, X. Dai, X. Chen, and X. Yang, "A hybrid teaching-learning artificial neural network for building electrical energy consumption prediction," Energy and Buildings, vol. 174, pp. 323-334, 2018/09/01/ 2018.
W. Wang, J. Chen, and T. Hong, "Occupancy prediction through machine learning and data fusion of environmental sensing and Wi-Fi sensing in buildings," Automation in Construction, vol. 94, pp. 233-243, 2018/10/01/ 2018.
S. Seyedzadeh, F. P. Rahimian, I. Glesk, and M. Roper, "Machine learning for estimation of building energy consumption and performance: a review," Visualization in Engineering, vol. 6, p. 5, 2018/10/02 2018.
Z. Ye and M. K. Kim, "Predicting electricity consumption in a building using an optimized back-propagation and Levenberg-Marquardt back-propagation neural network: Case study of a shopping mall in China," Sustainable Cities and Society, vol. 42, pp. 176-183, 2018/10/01/ 2018.
M. Negnevitsky, Artificial intelligence: a guide to intelligent systems, Second ed.: ADDISON WESLEY, 2005.
D. Geekiyanage and T. Ramachandra, "A model for estimating cooling energy demand at early design stage of condominiums," Journal of Building Engineering, vol. 17, pp. 43-51, 2018/05/01/ 2018.
D. Zhao, M. Zhong, X. Zhang, and X. Su, "Energy consumption predicting model of VRV (Variable refrigerant volume) system in office buildings based on data mining," Energy, vol. 102, pp. 660-668, 2016/05/01/ 2016.
B. B. Ekici and U. T. Aksoy, "Prediction of building energy consumption by using artificial neural networks," Advances in Engineering Software, vol. 40, pp. 356-362, 2009/05/01/ 2009.
A. E. Ben-Nakhi and M. A. Mahmoud, "Cooling load prediction for buildings using general regression neural networks," Energy Conversion and Management, vol. 45, pp. 2127-2141, 2004/08/01/ 2004.
C. Marino, A. Nucara, and M. Pietrafesa, "Does window-to-wall ratio have a significant effect on the energy consumption of buildings? A parametric analysis in Italian climate conditions," Journal of Building Engineering, vol. 13, pp. 169-183, 2017/09/01/ 2017.
S.-S. Lee, "Empirical validation of building energy simulation software; DOE2.E, HAP and TRACE " Ph.D, Iowa State University USA, 1998.
M. A. R. Biswas, M. D. Robinson, and N. Fumo, "Prediction of residential building energy consumption: A neural network approach," Energy, vol. 117, pp. 84-92, 2016/12/15/ 2016.
A. AlAnzi, D. Seo, and M. Krarti, "Impact of building shape on thermal performance of office buildings in Kuwait," Energy Conversion and Management, vol. 50, pp. 822-828, 2009/03/01/ 2009.
P. Depecker, C. Menezo, J. Virgone, and S. Lepers, "Design of buildings shape and energetic consumption," Building and Environment, vol. 36, pp. 627-635, 2001/06/01/ 2001.
T. Ahmad, H. Chen, R. Huang, G. Yabin, J. Wang, J. Shair, H. M. Azeem Akram, S. A. Hassnain Mohsan, and M. Kazim, "Supervised based machine learning models for short, medium and long-term energy prediction in distinct building environment," Energy, vol. 158, pp. 17-32, 2018/09/01/ 2018.
S. Paudel, M. Elmitri, S. Couturier, P. H. Nguyen, R. Kamphuis, B. Lacarrií¨re, and O. Le Corre, "A relevant data selection method for energy consumption prediction of low energy building based on support vector machine," Energy and Buildings, vol. 138, pp. 240-256, 2017/03/01/ 2017.
F. Yang, H. Cho, H. Zhang, J. Zhang, and Y. Wu, "Artificial neural network (ANN) based prediction and optimization of an organic Rankine cycle (ORC) for diesel engine waste heat recovery," Energy Conversion and Management, vol. 164, pp. 15-26, 2018/05/15/ 2018.
S. K. Lahiri and K. C. Ghanta, "Development of an artificial neural network correlation for prediction of hold-up of slurry transport in pipelines," Chemical Engineering Science, vol. 63, pp. 1497-1509, 2008/03/01/ 2008.
F. Z. R. Monteiro, I. C. Valim, R. N. C. Siqueira, F. J. Moura, A. V. Grillo, and B. F. Santos, "Application of artificial neural networks for identification of catalysts used in thermogravimetry lignocellulosic biomass," Chemical Engineering Transactions, vol. 65, pp. 529-534, 2018.
N. BAGYALAKSHMI and M. THIRUMARIMURUGAN, "FAULT DETECTION AND CONTROLLING OF SHELL AND TUBE HEAT EXCHANGER USING ANN," Journal Advances in Chemistry, vol. 12, pp. 5252-5260, 2016.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).