Evolutioinary Combination of Models in DSS based on Genetic Programming

摘要

The efficiency of model-aided decision making relies on the intelligent level of model selection. The purpose of this paper is to develop a new algorithm for model selection based on genetic programming. In the algorithm, the meta-models are classified according to the characteristics of the sample data, and the combined models are built as tree format. The genetic operations are performed under some constraints to produce combination models for users' reference. The process of the algorithm greatly decreases users' dependence on domain knowledge.