2023 Volume 35 Issue 4 Pages 742-745
The conventional multivariate analysis method using chemical data obtained by elemental analysis has been still challenging to discriminate materials are included in composite materials. Hierarchical cluster analysis (HCA) and Dempster–Shafer theory, that are series of multivariate analysis method, can evaluate the similarity of each material using the chemical data; however, are still difficult to identify the materials contained in a composite material. In this study, evaluating the similarity of elemental analysis data by HCA was conducted, and then stepwisely evaluating was implemented using degree of belief. In other words, it is a stepwise identification means of composite materials that combines the distance output from HCA with a concept of the degree of belief. Artificial model samples were demonstrated implementing in the result of standard reference materials such as metal alloys and plastics. Consequently, the proposed method consistently results prerequisites, and the degrees of belief were quantitatively calculated for each sample confirming the usefulness of this method.
