Behzad Radmehr - Department of Computer Engineering, Khorasan Razavi Science & Research Branch, Islamic Azad University Neyshabur , Iran
Reza Ghaemi - Department of Computer Engineering, Quchan Branch , Islamic Azad University, Quchan , Iran
Majid Mazinani - Department of Computer & Electrical Engineering, Imam Reza University , Mashhad , Iran

The intelligent hybrid methods are used for improving the performance of K-Means algorithm in this study. This research analyzed different kinds of scenarios of clustering mechanism. In data mining scope, fuzzy methods, evolutionary methods and neural network solutions can improve the performance of this algorithm. The purpose of this study is explained different intelligent methods and is discussed neural network solutions about it. Several neural network solutions existed in literature review. This study focuses on SOM (Self Organization Mapping), ELM (Extreme Learning Machines), deep learning and poly numerals networks. The purpose is evaluating a new hybrid method for K- Mean's algorithm.

Intelligent Hybrid Methods, Data Mining, K-Means Algorithm, Neural Network, Clustering Mechanism, Accuracy, Fuzzy C-Means Algorithm