HYBRIDIZATION OF MULTILAYER PERCEPTRON AND GENETIC ALGORITHM FOR LUNG CANCER DISEASE DIAGNOSIS USING MICRO-ARRAY DATASET

Authors

  • Ahmed Abiodun Taofik Department of Computer Science, School of ICT and Management Science, Kwara State College of Arabic and Islamic Legal Studies, Ilorin. Author
  • Issah Abolaji Yusuf Department of Computer Science, School of ICT and Management Science, Kwara State College of Arabic and Islamic Legal Studies, Ilorin. Author
  • Muhammed Kamaldeen Jimoh Department of Educational Technology, University of Ilorin, Ilorin, Nigeria. Author

Keywords:

Cancer, Diagnosis, Genetic Algorithm, Multilayer Perceptron, Hybridization

Abstract

This paper attempt a shift in paradigm from conventional methods by formulating hybridizing model of genetic algorithm and Multilayer perceptron for optimization of relevant features of the genes and classification of lung cancer disease respectively. Microarray data is to be considered as a dataset. The paper therefore, adopt hybridize model of Genetic Algorithm and MLP, it was developed and simulated in Weka environment using microarray cancer dataset. The solution found by the combined Genetic Algorithm and Multilayer Perceptron performed effectively well. The results presented in this paper revealed that the proposed hybridization of Genetic Algorithm and Multilayer Perceptron performs better with over 90% accuracy when used for classification of   microarray dataset of lung cancer.

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Published

2026-04-11