Image Classification Method using Dynamic Quantum Inspired Genetic Algorithm

• URL: http://arxiv.org/abs/2501.11477v4
• Date: Sat, 05 Apr 2025 03:55:20 GMT
• Title: Image Classification Method using Dynamic Quantum Inspired Genetic Algorithm
• Authors: Akhilesh Kumar Singh, Kirankumar R. Hiremath,
• Abstract summary: D-QIGA introduces adaptive mechanisms and a lengthening chromosome strategy to avoid local optima and improve optimization.<n>Tested on benchmark and real-world problems, it significantly outperforms traditional Genetic Algorithms, achieving over 99.99% classification accuracy compared to GA's 95%.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: This study presents a dynamic Quantum-Inspired Genetic Algorithm (D-QIGA) for feature selection, leveraging quantum principles like superposition and rotation gates to enhance exploration and exploitation. D-QIGA introduces adaptive mechanisms and a lengthening chromosome strategy to avoid local optima and improve optimization. Tested on benchmark and real-world problems, it significantly outperforms traditional Genetic Algorithms, achieving over 99.99% classification accuracy compared to GA's 95%.

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