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Hybrid Gravitational Search and Particle Swarm Based Fuzzy MLP for Medical Data Classification

  • Tirtharaj Dash
  • Sanjib Kumar Nayak
  • H. S. Behera
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 31)

Abstract

In this work, a hybrid training algorithm for fuzzy MLP, called Fuzzy MLP-GSPSO, has been proposed by combining two meta-heuristics: gravitational search (GS) and particle swarm optimization (PSO). The result model has been applied for classification of medical data. Five medical datasets from UCI machine learning repository are used as benchmark datasets for evaluating the performance of the proposed ‘Fuzzy MLP-GSPSO’ model. The experimental results show that Fuzzy MLP-GSPSO model outperforms Fuzzy MLP-GS and Fuzzy MLP-PSO for all the five datasets in terms of classification accuracy, and therefore can reduce overheads in medical diagnosis.

Keywords

Fuzzy multilayer perceptron Gravitational search Particle swarm optimization Breast cancer Heart disease Hepatitis Liver disorder Lung cancer Classification Medical data 

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Copyright information

© Springer India 2015

Authors and Affiliations

  • Tirtharaj Dash
    • 1
  • Sanjib Kumar Nayak
    • 2
  • H. S. Behera
    • 2
  1. 1.School of Computer ScienceNational Institute of Science and TechnologyBerhampurIndia
  2. 2.Department of Computer Science Engineering and Information TechnologyVeer Surendra Sai University of TechnologyBurlaIndia

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