Interpreting the pattern of volcano eruptions: Intelligent system for tephra layer correlation

The overall goal of the research presented in this paper is to design an intelligent system to aid geologists in processing complex rock characteristics for interpreting eruption patterns, and thereby to aid eruption forecasting for volcanic chains and fields. The objective of this paper is to describe application of data fusion techniques to designing an intelligent system. The processing of geological data described in this paper includes both a hybrid classifier for recognition of tephra layers utilizing lithostratigraphic tephra characteristics and clustering of geochemical features aimed at defining the size and position of potential zones of partial melt in volcanic regions. Special attention is paid to the description of a new evidential method of combining several clustering results. The method of fusion of several clustering results is not specific to geochemical data and can be used in other applications.