Creation of Prototypes of Case-Based Knowledge Bases Using Transformations of Decision Tables to Predict the Risk of Forest Fires

Improving the efficiency of the process of building knowledge bases of intelligent decision support systems continues to be an urgent scientific and technical task. The paper describes the application of an original approach that uses the principles of model-driven development and transformations to create prototypes of knowledge bases of a case-based type. The approach provides the transformation of specialized decision tables and conceptual models in order to obtain a base of cases of parametric form. A description of its main stages and an example of application in prototyping the knowledge base of the forest fire forecasting service are given.