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Novel Hybrid Genetic Arithmetic Optimization for Feature Selection and Classification of Pulmonary Disease Images

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  • S. Nivetha

    (Department of Computer Science, Periyar University, Salem, India)

  • H. Hannah Inbarani

    (Department of Computer Science, Periyar University, Salem, India)

Abstract

The difficulty in predicting early cancer is due to the lack of early illness indicators. Metaheuristic approaches are a family of algorithms that seek to find the optimal values for uncertain problems with several implications in optimization and classification problems. An automated system for recognizing illnesses can respond with accuracy, efficiency, and speed, helping medical professionals spot abnormalities and lowering death rates. This study proposes the Novel Hybrid GAO (Genetic Arithmetic Optimization algorithm based Feature Selection) (Genetic Arithmetic Optimization Algorithm-based feature selection) method as a way to choose the features for several machine learning algorithms to classify readily available data on COVID-19 and lung cancer. By choosing just important features, feature selection approaches might improve performance. The proposed approach employs a Genetic and Arithmetic Optimization to enhance the outcomes in an optimization approach.

Suggested Citation

  • S. Nivetha & H. Hannah Inbarani, 2023. "Novel Hybrid Genetic Arithmetic Optimization for Feature Selection and Classification of Pulmonary Disease Images," International Journal of Sociotechnology and Knowledge Development (IJSKD), IGI Global, vol. 15(1), pages 1-58, January.
    • Handle: RePEc:igg:jskd00:v:15:y:2023:i:1:p:1-58
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    References listed on IDEAS

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    1. Shifei Ding & Zhongzhi Shi & Ke Chen & Ahmad Taher Azar, 2015. "Mathematical Modeling and Analysis of Soft Computing," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-2, March.
    2. S. Nivetha & H. Hannah Inbarani, 2023. "Novel Adaptive Histogram Binning-Based Lesion Segmentation for Discerning Severity in COVID-19 Chest CT Scan Images," International Journal of Sociotechnology and Knowledge Development (IJSKD), IGI Global, vol. 15(1), pages 1-35, January.
    3. Prashant Kumar Shukla & Jasminder Kaur Sandhu & Anamika Ahirwar & Deepika Ghai & Priti Maheshwary & Piyush Kumar Shukla & Manjit Kaur, 2021. "Multiobjective Genetic Algorithm and Convolutional Neural Network Based COVID-19 Identification in Chest X-Ray Images," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-9, February.
    4. D. V. N. Ananth & Lagudu Venkata Suresh Kumar & Tulasichandra Sekhar Gorripotu & Ahmad Taher Azar, 2021. "Design of a Fuzzy Logic Controller for Short-Term Load Forecasting With Randomly Varying Load," International Journal of Sociotechnology and Knowledge Development (IJSKD), IGI Global, vol. 13(4), pages 32-49, October.
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    1. S. Nivetha & H. Hannah Inbarani, 2023. "Novel Adaptive Histogram Binning-Based Lesion Segmentation for Discerning Severity in COVID-19 Chest CT Scan Images," International Journal of Sociotechnology and Knowledge Development (IJSKD), IGI Global, vol. 15(1), pages 1-35, January.
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