Benchmarking whole-building energy performance with multi-criteria technique for order preference by similarity to ideal solution using a selective objective-weighting approach
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DOI: 10.1016/j.apenergy.2015.02.048
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- Dias, Luis C. & Domingues, Ana Rita, 2014. "On multi-criteria sustainability assessment: Spider-gram surface and dependence biases," Applied Energy, Elsevier, vol. 113(C), pages 159-163.
- Pisello, Anna Laura & Goretti, Michele & Cotana, Franco, 2012. "A method for assessing buildings’ energy efficiency by dynamic simulation and experimental activity," Applied Energy, Elsevier, vol. 97(C), pages 419-429.
- Chung, William & Hui, Y.V. & Lam, Y. Miu, 2006. "Benchmarking the energy efficiency of commercial buildings," Applied Energy, Elsevier, vol. 83(1), pages 1-14, January.
- Wong, S.L. & Wan, Kevin K.W. & Lam, Tony N.T., 2010. "Artificial neural networks for energy analysis of office buildings with daylighting," Applied Energy, Elsevier, vol. 87(2), pages 551-557, February.
- Chung, William, 2012. "Using the fuzzy linear regression method to benchmark the energy efficiency of commercial buildings," Applied Energy, Elsevier, vol. 95(C), pages 45-49.
- Chung, William, 2011. "Review of building energy-use performance benchmarking methodologies," Applied Energy, Elsevier, vol. 88(5), pages 1470-1479, May.
- Braun, M.R. & Altan, H. & Beck, S.B.M., 2014. "Using regression analysis to predict the future energy consumption of a supermarket in the UK," Applied Energy, Elsevier, vol. 130(C), pages 305-313.
- Li, Zhengwei & Han, Yanmin & Xu, Peng, 2014. "Methods for benchmarking building energy consumption against its past or intended performance: An overview," Applied Energy, Elsevier, vol. 124(C), pages 325-334.
- Ernest Reig‐Martínez & José A. Gómez‐Limón & Andrés J. Picazo‐Tadeo, 2011.
"Ranking farms with a composite indicator of sustainability,"
Agricultural Economics, International Association of Agricultural Economists, vol. 42(5), pages 561-575, September.
- Ernest Reig-Martínez & José A. Gómez-Limón & Andrés J. Picazo-Tadeo, 2010. "Ranking farms with a composite indicator of sustainability," Working Papers 1005, Department of Applied Economics II, Universidad de Valencia.
- Gaitani, N. & Lehmann, C. & Santamouris, M. & Mihalakakou, G. & Patargias, P., 2010. "Using principal component and cluster analysis in the heating evaluation of the school building sector," Applied Energy, Elsevier, vol. 87(6), pages 2079-2086, June.
- Estiri, Hossein, 2014. "Building and household X-factors and energy consumption at the residential sector," Energy Economics, Elsevier, vol. 43(C), pages 178-184.
- Lee, Wen-Shing & Lin, Yeong-Chuan, 2011. "Evaluating and ranking energy performance of office buildings using Grey relational analysis," Energy, Elsevier, vol. 36(5), pages 2551-2556.
- Gómez-Limón, José A. & Sanchez-Fernandez, Gabriela, 2010. "Empirical evaluation of agricultural sustainability using composite indicators," Ecological Economics, Elsevier, vol. 69(5), pages 1062-1075, March.
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Keywords
Benchmarking; Whole-building energy performance; Multi-criteria; TOPSIS; Objective-weighting;All these keywords.
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