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author:

Zhang, Xiang (Zhang, Xiang.) [1] | Huang, Jianhua (Huang, Jianhua.) [2] (Scholars:黄建华)

Indexed by:

EI Scopus SCIE

Abstract:

The occurrence of safety incidents for existing glass curtain walls (EGCWs) pronounced menace to the security of both lives and property. Undertaking safety assessment for EGCWs carries essential practical significance. However, current fuzzy evaluation methods overlook the uncertainty of indicator weights and the intricacies of rank attribution. In response, this paper proposes a novel approach to the safety assessment of EGCWs. This research establishes a framework of evaluation indicators for EGCWs and divides the safety ranks of each indicator into four tiers: Safe, Mild risk, Moderate risk, and High risk. Quantitative and qualitative indicators are quantified via the variable fuzzy cloud algorithm and cloud model. The information cloud combination weighting method is introduced to determine the weight clouds of indicators. Finally, a two-dimensional assessment result is derived using an improved fuzzy comprehensive evaluation method and fuzzy entropy. The exemplified outcomes demonstrate that this approach captures the safety status of evaluation subjects based on risk ranks, and fuzzy entropy addresses two issues: inconsistent level attribution and the comparison of identical risk ranks. The appraisal method further unveils the safety details of EGCWs, with findings that align consistently with the actual situation.

Keyword:

cloud model existing glass curtain wall fuzzy entropy Safety evaluation variable fuzzy cloud algorithm

Community:

  • [ 1 ] [Zhang, Xiang]Fuzhou Univ, Sch Econ & Management, 2 Longjing Ave, Fuzhou, Peoples R China
  • [ 2 ] [Huang, Jianhua]Fuzhou Univ, Sch Econ & Management, 2 Longjing Ave, Fuzhou, Peoples R China

Reprint 's Address:

  • 张翔

    [Zhang, Xiang]Fuzhou Univ, Sch Econ & Management, 2 Longjing Ave, Fuzhou, Peoples R China

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Source :

JOURNAL OF INTELLIGENT & FUZZY SYSTEMS

ISSN: 1064-1246

Year: 2024

Issue: 2

Volume: 46

Page: 5125-5137

1 . 7 0 0

JCR@2023

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 5

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