{"title":"通过三角分布生成不精确数据的新算法","authors":"Muhammad Aslam","doi":"10.1109/TBDATA.2024.3460529","DOIUrl":null,"url":null,"abstract":"The manuscript introduces the mathematical representation of the neutrosophic triangular distribution, encompassing probability density functions and cumulative distribution functions. Two algorithms are introduced for the generation of random variates based on this distribution. Through simulations and a comparative examination with traditional statistical approaches, the research illustrates the versatility and resilience of the neutrosophic triangular distribution. The findings underscore its effectiveness in addressing uncertainty, particularly in scenarios with varying degrees of indeterminacy. The study emphasizes the substantial influence of uncertainty on the generation of random variates, with potential implications for decision-making and data analysis.","PeriodicalId":13106,"journal":{"name":"IEEE Transactions on Big Data","volume":"11 3","pages":"1411-1418"},"PeriodicalIF":7.5000,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Developing Novel Algorithms for Generating Inexact Data Through Triangle Distribution\",\"authors\":\"Muhammad Aslam\",\"doi\":\"10.1109/TBDATA.2024.3460529\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The manuscript introduces the mathematical representation of the neutrosophic triangular distribution, encompassing probability density functions and cumulative distribution functions. Two algorithms are introduced for the generation of random variates based on this distribution. Through simulations and a comparative examination with traditional statistical approaches, the research illustrates the versatility and resilience of the neutrosophic triangular distribution. The findings underscore its effectiveness in addressing uncertainty, particularly in scenarios with varying degrees of indeterminacy. The study emphasizes the substantial influence of uncertainty on the generation of random variates, with potential implications for decision-making and data analysis.\",\"PeriodicalId\":13106,\"journal\":{\"name\":\"IEEE Transactions on Big Data\",\"volume\":\"11 3\",\"pages\":\"1411-1418\"},\"PeriodicalIF\":7.5000,\"publicationDate\":\"2024-09-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Big Data\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10679704/\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Big Data","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10679704/","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Developing Novel Algorithms for Generating Inexact Data Through Triangle Distribution
The manuscript introduces the mathematical representation of the neutrosophic triangular distribution, encompassing probability density functions and cumulative distribution functions. Two algorithms are introduced for the generation of random variates based on this distribution. Through simulations and a comparative examination with traditional statistical approaches, the research illustrates the versatility and resilience of the neutrosophic triangular distribution. The findings underscore its effectiveness in addressing uncertainty, particularly in scenarios with varying degrees of indeterminacy. The study emphasizes the substantial influence of uncertainty on the generation of random variates, with potential implications for decision-making and data analysis.
期刊介绍:
The IEEE Transactions on Big Data publishes peer-reviewed articles focusing on big data. These articles present innovative research ideas and application results across disciplines, including novel theories, algorithms, and applications. Research areas cover a wide range, such as big data analytics, visualization, curation, management, semantics, infrastructure, standards, performance analysis, intelligence extraction, scientific discovery, security, privacy, and legal issues specific to big data. The journal also prioritizes applications of big data in fields generating massive datasets.