Assumption retrieval from process models

摘要

Process models of lumped systems are considered in this paper in their "canonical" form where the equations and variables are classified, the "natural" set of design variables and "natural" assignment are selected. An efficient intelligent algorithm is proposed to generate the assumption sequences leading from one model to another in an automated way. The algorithm has been implemented in PROLOG within our intelligent model editor. Two simple assumption retrieval examples are also presented and discussed for analyzing and comparison purposes.