Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Article type: Research Article
Authors: Lee, Pin-Chana; b | Zhao, Yijingc | Lo, Tzu-Pingd; * | Long, Danbingc
Affiliations: [a] School of Civil Engineering, Southwest Jiaotong University, Chengdu, China | [b] School of Civil Engineering, Chongqing University, China | [c] School of Civil Engineering, Southwest Jiaotong University, Chengdu, China | [d] Chengdu Liangzi Intelligent Technology Ltd, Chengdu, Sichuan, China
Correspondence: [*] Corresponding author. Tzu-Ping Lo, Chengdu Liangzi Intelligent Technology Ltd, No. 111, First Section, North of Second Ring Road, Chengdu, Sichuan, 610031, China. Cellphone: +86-18280009907; E-mail: 2731368845@qq.com.
Abstract: The construction industry has long been seen as a high-risk industry, and the risk evaluation method is the core of safety risk management. Complex construction environments can lead to risk evolution over time, leading to uncertainty in risk assessment. Therefore, it is necessary to establish a risk evaluation method for multi-period group decision, which can also deal with uncertain information reliably. This study defines the risk evaluation indicators for construction safety and adopts the cloud model to deal with the uncertain information of experts’ evaluations. A cloud-based aggregation algorithm is also employed for group decision. Then, a cloud-based Minkowski distance function is proposed to enhance the ability of TOPSIS to deal with the uncertain information. Finally, an optimization algorithm is used to calculate the multi-period comprehensive evaluation value to define the risk priority. A real case is used for demonstration and the results show that the proposed method can effectively deal with the risk evaluation problem of multi-project, multi-period and group decision with uncertain information.
Keywords: Construction safety risk, cloud model, TOPSIS, uncertain information
DOI: 10.3233/JIFS-190076
Journal: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 5203-5215, 2019
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
sales@iospress.com
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
info@iospress.nl
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office info@iospress.nl
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
china@iospress.cn
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
如果您在出版方面需要帮助或有任何建, 件至: editorial@iospress.nl