Efficient protocol for data clustering by fuzzy Cuckoo Optimization Algorithm |
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| Affiliation: | 1. Department of Computer Engineering, Nourabad Mamasani Branch, Islamic Azad University, Nourabad Mamasani, Iran;2. Computer Engineering Department, Boukan Branch, Islamic Azad University, Boukan, Iran;1. Institute of Advanced Technology, Nanjing University of Posts and Telecommunications, Nanjing 210003, PR China;2. School of Mechatronic Engineering and Automation, Shanghai University, 200072, PR China;1. Labget Laboratory, Department of Electrical Engineering, University Larbi Tebessi, Tébessa, Algeria;2. Telecommunication Laboratory, University 8 May 1945, Guelma, Algeria;1. Department of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou 325035, China;2. Wenzhou Radio &TV University, Wenzhou 325035, China;3. Wenzhou Polytechnic, Wenzhou 325035, China;4. School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran;5. Department of Computer Science, School of Computing, National University of Singapore, Singapore, Singapore;6. Institute of Research and Development, Duy Tan University, Da Nang 550000, Viet Nam;7. Department of Pulmonary and Critical Care Medicine, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, China |
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| Abstract: | Data clustering is a technique for grouping similar and dissimilar data. Many clustering algorithms fail when dealing with multi-dimensional data. This paper introduces efficient methods for data clustering by Cuckoo Optimization Algorithm; called COAC and Fuzzy Cuckoo Optimization Algorithm, called FCOAC. The COA by inspire of cuckoo bird nature life tries to solve continuous problems. This algorithm clusters a large dataset to prior determined clusters numbers by this meta-heuristic algorithm and optimal the results by fuzzy logic. Firstly, the algorithm generates a random solutions equal to cuckoo population and with length dataset objects and with a cost function calculates the cost of each solution. Finally, fuzzy logic tries for the optimal solution. The performance of our algorithm is evaluated and compared with COAC, Black hole, CS, K-mean, PSO and GSA. The results show that our algorithm has better performance in comparison with them. |
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| Keywords: | Data clustering Cuckoo Optimization Algorithm (COA) Dataset Fuzzy logic Artificial intelligence |
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