Title: Enhancing Sorting Algorithms with Artificial Intelligence: A Hybrid Approach
Authors: Amal Dwimah, Samy S. Abu-Naser
Volume: 9
Issue: 8
Pages: 64-69
Publication Date: 2025/08/28
Abstract:
This paper presents a hybrid approach to combine artificial intelligence with traditional sorting algorithms to improve their performance in large-scale data environments. The approach integrates the classical QuickSort algorithm with AI techniques such as machine learning and deep learning to intelligently select the pivot based on data characteristics. Experimental results on three distinct datasets (random, partially sorted, and highly skewed) show an average 28% improvement in sorting time compared to traditional sorting algorithms. The model demonstrated a significant performance boost (up to 65%) on non-random data patterns, while maintaining QuickSort's average-case time complexity of O(n log n).