{"title":"双向增强选择排序算法技术","authors":"Ramcis N. Vilchez","doi":"10.20469/ijaps.5.50004-1","DOIUrl":null,"url":null,"abstract":"Sorting algorithm refers to the arranging of numerical or alphabetical or character data in statistical order (ascending or descending). Sorting algorithm plays a vital role in searching and the field of data science. Most of the sorting algorithms with O(n2) time complexity are very efficient for a small list of elements. However, for large data, these algorithms are very inefficient. This study presented a remedy for the noted deficiencies of O(n2) sort algorithm for large data. Among the O(n2) algorithms, selection sort was the subject of the study considering its simplicity. Although selection sort is regarded as the most straightforward algorithm, it is also considered the second worst algorithm in terms of time complexity for large data. Several enhancements were conducted to address the inefficiencies of selection sort. However, the procedures presented in all the enhancements can still lead to some unnecessary comparisons, and iterations that cause poor sorting performance. The modified selection sort algorithm utilizes a Bidirectional Enhanced Selection Sort Algorithm Technique to reduce the number of comparisons and iterations that causes sorting delays. The modified algorithm was tested using varied data to validate the performance. The result was compared with the other O(n2) algorithm. The results show that the modified algorithm has a significant run time complexity improvement compared with the other O(n2) algorithms. This study has a significant contribution to the field of data structures in computer science and the field of data science.","PeriodicalId":228173,"journal":{"name":"International Journal of Applied and Physical Sciences","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Bidirectional Enhanced Selection Sort Algorithm Technique\",\"authors\":\"Ramcis N. Vilchez\",\"doi\":\"10.20469/ijaps.5.50004-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Sorting algorithm refers to the arranging of numerical or alphabetical or character data in statistical order (ascending or descending). Sorting algorithm plays a vital role in searching and the field of data science. Most of the sorting algorithms with O(n2) time complexity are very efficient for a small list of elements. However, for large data, these algorithms are very inefficient. This study presented a remedy for the noted deficiencies of O(n2) sort algorithm for large data. Among the O(n2) algorithms, selection sort was the subject of the study considering its simplicity. Although selection sort is regarded as the most straightforward algorithm, it is also considered the second worst algorithm in terms of time complexity for large data. Several enhancements were conducted to address the inefficiencies of selection sort. However, the procedures presented in all the enhancements can still lead to some unnecessary comparisons, and iterations that cause poor sorting performance. The modified selection sort algorithm utilizes a Bidirectional Enhanced Selection Sort Algorithm Technique to reduce the number of comparisons and iterations that causes sorting delays. The modified algorithm was tested using varied data to validate the performance. The result was compared with the other O(n2) algorithm. The results show that the modified algorithm has a significant run time complexity improvement compared with the other O(n2) algorithms. This study has a significant contribution to the field of data structures in computer science and the field of data science.\",\"PeriodicalId\":228173,\"journal\":{\"name\":\"International Journal of Applied and Physical Sciences\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Applied and Physical Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.20469/ijaps.5.50004-1\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Applied and Physical Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.20469/ijaps.5.50004-1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Sorting algorithm refers to the arranging of numerical or alphabetical or character data in statistical order (ascending or descending). Sorting algorithm plays a vital role in searching and the field of data science. Most of the sorting algorithms with O(n2) time complexity are very efficient for a small list of elements. However, for large data, these algorithms are very inefficient. This study presented a remedy for the noted deficiencies of O(n2) sort algorithm for large data. Among the O(n2) algorithms, selection sort was the subject of the study considering its simplicity. Although selection sort is regarded as the most straightforward algorithm, it is also considered the second worst algorithm in terms of time complexity for large data. Several enhancements were conducted to address the inefficiencies of selection sort. However, the procedures presented in all the enhancements can still lead to some unnecessary comparisons, and iterations that cause poor sorting performance. The modified selection sort algorithm utilizes a Bidirectional Enhanced Selection Sort Algorithm Technique to reduce the number of comparisons and iterations that causes sorting delays. The modified algorithm was tested using varied data to validate the performance. The result was compared with the other O(n2) algorithm. The results show that the modified algorithm has a significant run time complexity improvement compared with the other O(n2) algorithms. This study has a significant contribution to the field of data structures in computer science and the field of data science.