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Critical Factors of the Application of Nanotechnology in Construction Industry By Using Anp Technique Under Fuzzy Intuitionistic Environment

Author(s):






Medium: journal article
Language(s): Latvian
Published in: Journal of Civil Engineering and Management, , n. 7, v. 23
Page(s): 914-925
DOI: 10.3846/13923730.2017.1343202
Abstract:

Nanotechnology plays a significant role in construction industry. The construction industry has been employed nanomaterials to improve the performance of construction components and the safety of the structure and to reduce the energy consuming and the cost of maintenance. In other words, nanotechnology has a substantial impact on the construc­tion industry. Therefore, it is necessary to identify and evaluate the critical factors of the application of nanotechnology in construction in order to concentrate on the most critical factors. However, several techniques have been developed to prioritize the evaluation criteria. Analytical network process (ANP) technique, a branch of multi criteria decision mak­ing (MCDM) methods, is a powerful tool to rank a limited number of criteria. This technique takes into account both tangible and intangible criteria in the process of formulation of a decision making problem. This method is capable of handling all types of independence and dependence relationships. On the other hand, intuitionistic fuzzy set (IFS) is a well-known technique in considering the inherent uncertainty involved in the process of modelling a decision making problem. In this paper, a new model based on the IFS and ANP technique is proposed to evaluate the critical factors of the application of nanotechnology in the construction industry. The results demonstrate that the proposed model has a high potential for taking into account the uncertainty in the form of a three dimension function, including membership, non-membership, and non-determinacy.

Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.3846/13923730.2017.1343202.
  • About this
    data sheet
  • Reference-ID
    10354262
  • Published on:
    13/08/2019
  • Last updated on:
    13/08/2019
 
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