Environmental assessment under uncertainty using Dempster–Shafer theory and Z-numbers

  • Bingyi KangEmail author
  • Pengdan Zhang
  • Zhenyu Gao
  • Gyan Chhipi-Shrestha
  • Kasun Hewage
  • Rehan Sadiq
Original Research


Environmental assessment and decision making is complex leading to uncertainty due to multiple criteria involved with uncertain information. Uncertainty is an unavoidable and inevitable element of any environmental evaluation process. The published literatures rarely include the studies on uncertain data with variable fuzzy reliabilities. This research has proposed an environmental evaluation framework based on Dempster–Shafer theory and Z-numbers. Of which a new notion of the utility of fuzzy number is proposed to generate the basic probability assignment of Z-numbers. The framework can effectively aggregate uncertain data with different fuzzy reliabilities to obtain a comprehensive evaluation measure. The proposed model has been applied to two case studies to illustrate the proposed framework and show its effectiveness in environmental evaluations. Results show that the proposed framework can improve the previous methods with comparability considering the reliability of information using Z-numbers. The proposed method is more flexible comparing with previous work.


Environmental assessment Environmental risk Dempster–Shafer theory Z-number Data fusion Fuzzy reliability 



The work is supported by a startup fund from Northwest A&F University (no. Z109021812).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

About the dataset used for model development

The data related to CDI were obtained from the Interior Health Authority (IHA), British Columbia. The database included the retrospective data of 22 hospitals spanned over 10 fiscal quarters from April 2012 to June 2014. The data were comprised of nursing staff to beds ratio (full-time); hand hygiene compliance; amount of Fluoroquinolone and Cephalosporins, and CDI cases. All cases of CDI were identified by Infection Prevention and Control, IHA. CDI incidence (output variable) was expressed in terms of number of CDI cases per 10,000 patient-days. For conveyance, the CDI related data of different hospitals of Quarter 2 of the fiscal year 2013 is given as an example in Table 12.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.College of Information EngineeringNorthwest A&F UniversityYanglingChina
  2. 2.School of EngineeringUniversity of British Columbia OkanaganKelownaCanada

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