Knowledge-Based Approach to Selection of Weight-in-Motion Equipment

The paper deals with the knowledge-based approach applied to selection of a proper equipment for measurement of road vehicles weights, preferably based on a weight-in-motion principle. After brief introduction the authors identify potentially usable attributes whose values create a data set characterizing particularly collected measurement equipment. The data mining software is used to create the initial version of the decision tree that is further manually modified to change "a classification model" to "a selection model" providing more information needed for user's decision making. The knowledge is then transformed into the rule-base form, implemented and validate by a rule-based expert system shell.