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Linguistic intuitionistic fuzzy PROMETHEE method based on similarity measure for the selection of sustainable building materials

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Abstract

The selection of sustainable building materials has attracted much attention from society because it is essential for environment, economy, and human health. To meet the need of the building development, the identified criteria for optimal sustainable building materials are determined based on sustainability building standards and previous studies including economic, environmental, social, and technological aspects. To represent the qualitative preferred and non-preferred cognitions of the decision makers, linguistic intuitionistic fuzzy numbers (LIFNs) are utilized to describe the evaluation information, which is a powerful and flexible tool. Then, new accuracy function and score function are defined to rank LIFNs more objectively. In addition, this paper employs a new linguistic intuitionistic fuzzy entropy to calculate the weights of criteria, and models based on the Shapley function with respect to 2-additive measure are constructed to reflect the correlations among elements in a set. Based on these results, a linguistic intuitionistic fuzzy Preference Ranking Organization Method for Enrichment Evaluation and prospect theory based hybrid method is proposed to assess the sustainable building materials. Finally, the effectiveness of the new method is testified by a case study for sustainable indoor flooring material selection, and comparative analysis is made.

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Acknowledgements

The authors gratefully thank the Editor-in-Chief Professor Vincenzo Loia, the Associated Editor Professor Aniello Castiglione, and three anonymous referees for their valuable and constructive comments, which have much improved the paper. This work was supported by the Major Project for National Natural Science Foundation of China (no. 72091515).

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Correspondence to Binghua Dong.

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Meng, F., Dong, B. Linguistic intuitionistic fuzzy PROMETHEE method based on similarity measure for the selection of sustainable building materials. J Ambient Intell Human Comput 13, 4415–4435 (2022). https://doi.org/10.1007/s12652-021-03338-y

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