Enhanced hierarchical fuzzy model using evolutionary GA with modified ABC algorithm for classification problem

This paper enhances the hierarchical fuzzy model to deal with the classification problems by adopting evolutionary genetic algorithm (GA) with a modified artificial bee colony (ABC) algorithm. Traditionally, fuzzy classifier could not provide a sufficiently high classification rate in higher feature dimension with few rules. In the literature, the genetic algorithm can take advantage from the global searching; moreover, the characteristic of ABC can enhance the local searching. Therefore, the hierarchical fuzzy model integrates GA with a modified ABC algorithm is constructed in this study to recognize some classification problems. The classification simulation includes three benchmark databases such as Glass, Wine, and Iris database. The result demonstrates that using evolutionary GA and modified ABC algorithm is beneficial than that without turning. Therefore, it is clearly that our methodology considers not only the global exploration but also the local exploitation.