Z-ACM: An approximate calculation method of Z-numbers for large data sets based on kernel density estimation and its application in decision-making

. The main ideas are as follows: first, kernel density estimation is used to partition/group Z-numbers with the total utility of Z-numbers; second, aggregate the representative Z-number in each partitioned interval using the classical arithmetic framework of Z-numbers. Based on the proposed Z-ACM, a fast decision model (FDM) is designed to deal with the issue of multi-criteria decision-making. Some examples with comparative analysis and rationality analysis are conducted to illustrate the effectiveness of the proposed methodology.