Title of article :
A hybrid model of genetic algorithm with local search to discover linguistic data summaries from creep data
Author/Authors :
Donis-Dيaz، نويسنده , , C.A. and Muro، نويسنده , , A.G. and Bello-Pérez، نويسنده , , R. and Morales، نويسنده , , E.V.، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2014
Abstract :
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.
Keywords :
Genetic algorithms , Linguistic data summarization , DATA MINING , Fuzzy Logic , Creep rupture stress
Journal title :
Expert Systems with Applications
Journal title :
Expert Systems with Applications