Title: AI-Driven Sorting Algorithms for Big Data: Techniques and Real- World Applications
Authors: Shatha Khalafallah and Samy S. Abu-Naser
Volume: 9
Issue: 6
Pages: 1-10
Publication Date: 2025/06/28
Abstract:
This research paper examines AI-driven sorting algorithms tailored for big data, exploring the fusion of traditional and cutting-edge methods to enhance data processing. The focus is on the performance of QuickSort, MergeSort, and AI-augmented algorithms like deep neural networks (DNNs) and reinforcement learning (RL) models across various data types and sizes. Our methodology emphasizes diverse real-world and synthetic datasets to assess execution time, memory usage, and computational efficiency. The findings illustrate how AI techniques can offer significant advantages in processing large- scale data, especially in dynamic, multimodal scenarios [1].