Affiliations: [a]
School of Science, Nanjing University of Science and Technology, Nanjing, Jiangsu, China
| [b]
School of Science, Nanjing Forestry University, Nanjing, Jiangsu, China
Correspondence:
[*]
Corresponding author. Yuanguo Zhu, School of Science, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu, China. E-mail: [email protected].
Abstract: The uncertainty theory is a branch of mathematics for studying subjective uncertainty phenomenon, and its role in subjective uncertain problems helps people make better decisions. But in real life, there is not a standard method to deal with multiple experts’ data problem. A simple method is to average all experts’ data to get a result. The other is to use the Delphi method to collect data many times and then get a normal result. This paper gives two new methods to handle this problem through conditional distributions. Compared to traditional method, they do not require all experts’ data from the beginning and the result obtained by these methods can be updated easily when new expert’s data is given.
