A hybrid model of genetic algorithm with local search to discover linguistic data summaries from creep data

• A hybrid model of genetic algorithm with local search to discover linguistic summaries is proposed.
• Specific operators and fitness function for the genetic algorithm were proposed.
• The proposed model improve the search of linguistic summaries on creep data compared with the classical model.
• The results were validated through the physical interpretation of some obtained summaries.

A hybrid model of Genetic Algorithm (GA) with local search to discover linguistic summaries and its application into the creep data analysis is proposed in this paper. Two specifics operator and a called Diversity term in the fitness function are introduced by the model to guarantees summaries with high quality and a wide range of information respectively. The experiments show that the hybrid model improves the results compared to those obtained using the classical model of GA. The quality of the summaries was verified by the interpretation of some of them from the theoretical point of view.