A Sorting Algorithm Based on Calculation
Sheng Bao, De-Shun Zheng

TL;DR
This paper presents an adaptive sorting algorithm that uses a guessing function to accurately relocate elements, achieving linear time complexity under uniform distribution, with potential applications in searching algorithms.
Contribution
It introduces a novel sorting method based on a guessing function that maps values to sorted positions, offering linear time complexity for uniform data distributions.
Findings
Achieves O(n) sorting time for uniformly distributed data
Uses a guessing function to map values to sorted positions
Potentially applicable to efficient searching algorithms
Abstract
This article introduces an adaptive sorting algorithm that can relocate elements accurately by substituting their values into a function which we name it the guessing function. We focus on building this function which is the mapping relationship between record values and their corresponding sorted locations essentially. The time complexity of this algorithm O(n),when records distributed uniformly. Additionally, similar approach can be used in the searching algorithm.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Algorithms and Applications
