Research Article
Fuzzy Honey Bees Foraging Optimization: Swarm Intelligence Approach for Clustering

Ali-Asghar Gholami, Ramin Ayanzadeh and Elaheh Raisi

Journal of Artificial Intelligence, 2014, 7(1), 13-23.


Clustering is one of the most important steps in data mining; it is known for its phenomenal functionalities in complex real world applications including biology, basic science, medicine, engineering and social science. In this sense, owing to the remarkable effects of clustering on data mining area, wide varieties of clustering approaches have been introduced to cluster data into significant subsets in order to obtain useful information. In this study, a novel clustering method based on honey bees foraging optimization algorithm and fuzzy rules is proposed. In the proposed method, fine shade of local and global search in honey bees optimization algorithm is schemed to be applied to improve the clustering efficiency. Furthermore, fuzzy operators are employed to enhance the performance of new proposed approach and prevent premature convergence. To verify and validate the functionality proposed of method, new method is run on three known data sets of the UCI Machine Learning Repository. Results of clustering reveal that proposed method estimate more desirable clusters compared to the state of the art clustering methods. Moreover, this method appears very stable in multiple tests.

ASCI-ID: 33-136

Cited References Fulltext

Similar Articles

Automated Clustering of Cancer Cells Using Fuzzy C Means with Repulsions in Ultrasound Images

Journal of Artificial Intelligence, 2012, 5(1), 14-25.

Applicability of Ensemble Clustering and Ensemble Classification Algorithm for User Navigation Pattern Prediction

Journal of Artificial Intelligence, 2013, 6(3), 210-219.

Automatic Multi-Document Arabic Text Summarization Using Clustering and Keyphrase Extraction

Journal of Artificial Intelligence, 2015, 8(1), 1-9.

Enrollment Forecasting based on Modified Weight Fuzzy Time Series

Journal of Artificial Intelligence, 2011, 4(1), 110-118.

The Development of a Particle Swarm Based Optimization Strategy for Pairwise Testing

Journal of Artificial Intelligence, 2011, 4(2), 156-165.

Recognition of Marathi Numerals Using Artificial Neural Network

Journal of Artificial Intelligence, 2010, 3(3), 135-140.

Handwritten Devanagari Character Recognition using Artificial Neural Network

Journal of Artificial Intelligence, 2011, 4(1), 55-62.

Using Probabilistic Neural Networks for Handwritten Digit Recognition

Journal of Artificial Intelligence, 2011, 4(4), 288-294.