Reduced fuzzy rule base design using Hybrid Elite Genetic Algorithm and Tabu Search

Author(s):  
Nesrine TALBI ◽  
Khaled BELARBI
2016 ◽  
Author(s):  
Leonardo G. Melo ◽  
Luís A. Lucas ◽  
Myriam R. Delgado

2014 ◽  
Vol 513-517 ◽  
pp. 1392-1397
Author(s):  
Shu Xia Liu ◽  
Yong Yang ◽  
Dian Bao Mu ◽  
Pan Chi Li

Based on the learning and integrated application of the T-S modeling method and Phase based Quantum Genetic Algorithm (PQGA), this article aims to provide a new and effective method to fulfill the actual demand of the oilfield development and production. First, according to the forecast indicators and the influencing factors, establish the fuzzy rule base, then according to the fuzzy rule base, establish the T-S prediction model, with improved quantum genetic algorithm to optimize the parameters of the T-S model, through the application of the prediction of the water-cut in oilfield, we prove that the method is effective.


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