通过三角分布生成不精确数据的新算法

IF 7.5 3区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Muhammad Aslam
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引用次数: 0

摘要

本文介绍了中性粒细胞三角形分布的数学表示,包括概率密度函数和累积分布函数。介绍了两种基于该分布的随机变量生成算法。通过模拟和与传统统计方法的比较检验,研究说明了中性粒细胞三角形分布的多功能性和弹性。研究结果强调了它在解决不确定性方面的有效性,特别是在不同程度不确定性的情况下。该研究强调了不确定性对随机变量产生的实质性影响,对决策和数据分析具有潜在的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
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来源期刊
CiteScore
11.80
自引率
2.80%
发文量
114
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.
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