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Evolving Neural Networks in Classification

This research focuses on developing Evolving Neural Networks (ENNs) to improve classification tasks in data mining. As a Ph.D. candidate in Engineering Management with a Master's in Computer Engineering, I have extensive experience as a research assistant, contributing to projects in the Smart Engineering Systems Lab and the Computational Intelligence Lab. My work includes the design and implementation of a hybrid intelligent system that integrates neural networks and genetic algorithms for automatic cell classification and other customizable tasks, leveraging feature selection and adaptable topology.

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Evolving Neural Networks in Classification

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  1. Evolving Neural Networks in Classification Sunghwan Sohn

  2. Education • Ph.D. Candidate, Engineering Management • M.S., Computer Engineering • B.E., Electronics Engineering

  3. Experience • Research Assistant in Smart Engineering Systems Lab • Developing Evolving Neural Networks in Data Mining • Research Assistant in Computational Intelligence Lab • Developed Automatic White Blood Cell Classification System

  4. Research • Objective: To develop a hybrid intelligent system – Evolving Neural Networks (ENNs) – that can be used in data mining, especially in classification problems.

  5. Research (ENNs) • Employs computational intelligence methodologies • Neural Networks & Genetic Algorithms • Genetic algorithms have been applied to automatic generation of neural networks • Feature selection • Adaptable topology • Customized tasks • Ensemble method

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