A Clustering Based Classification Approach Based on Modified Cuckoo Search Algorithm


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Аннотация

Cuckoo Search Algorithm (CSA) is one of the new swarm intelligence based optimization algorithms, which has shown an effective performance on many optimization problems. However, the effectiveness of CSA significantly depends on the exploration and exploitation potential and it may also possible to increase its efficiency when solving complex optimization problems. In this study, some mechanisms have been employed on CSA to increase its efficiency such as use of global best and individual best solutions to guide the other solutions, self-adaption techniques for parameters and so on. The modified CSA (i.e., MCSA) is successfully employed in clustering based classification domain. The experimental results and execution time prove its effectiveness over existing modified CSAs and other employed swarm intelligence algorithms. The proposed clustering model is also employed in color histopathological image segmentation domain and provides effective result.

Авторлар туралы

Krishna Dhal

Department of Computer Science and Application, Midnapore College (Autonomous)

Хат алмасуға жауапты Автор.
Email: krishnagopal.dhal@midnaporecollege.ac.in
Үндістан, Paschim Medinipur, West Bengal

Arunita Das

Department of Information Technology, Kalyani Government Engineering College

Хат алмасуға жауапты Автор.
Email: arunita17@gmail.com
Үндістан, Kalyani, Nadia

Swarnajit Ray

Skybound Digital LLC Pvt. Ltd.

Хат алмасуға жауапты Автор.
Email: swarnajit32@gmail.com
Үндістан, Kolkata, West Bengal

Sanjoy Das

Department of Engineering and Technological Studies, University of Kalyani

Хат алмасуға жауапты Автор.
Email: dassanjoy0810@hotmail.com
Үндістан, Kalyani, Nadia

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