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Linguistic neutrosophic power Muirhead mean operators for safety evaluation of mines

机译:语言中智能力Muirhead是用于评估矿山安全性的算子

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摘要

Safety is the fundamental guarantee for the sustainable development of mining enterprises. As the safety evaluation of mines is a complex system engineering project, consistent and inconsistent, even hesitant evaluation information may be contained simultaneously. Linguistic neutrosophic numbers (LNNs), as the extensions of linguistic terms, are effective means to entirely and qualitatively convey such evaluation information with three independent linguistic membership functions. The aim of our work is to investigate several mean operators so that the safety evaluation issues of mines are addressed under linguistic neutrosophic environment. During the safety evaluation process of mines, many influence factors should be considered, and some of them may interact with each other. To this end, the Muirhead mean (MM) operators are adopted as they are powerful tools to deal with such situation. On the other hand, to diminish the impacts of irrational data provided by evaluators, the power average (PA) operators are under consideration. Thus, with the combination of MM and PA, the power MM operators and weighted power MM operators are proposed to aggregate linguistic neutrosophic information. Meanwhile, some key points and special cases are studied. The advantages of these operators are that not only the interrelations among any number of inputs can be reflected, but also the effects of unreasonable information can be reduced. Thereafter, a new linguistic neutrosophic ranking technique based on these operators is developed to evaluate the mine safety. Moreover, in-depth discussions are made to show the robust and flexible abilities of our method. Results manifest that the proposed method is successful in dealing with mine safety evaluation issues within linguistic neutrosophic circumstances.
机译:安全是矿业企业可持续发展的根本保证。由于矿山的安全评估是一项复杂的系统工程项目,因此可能会同时包含一致和不一致甚至犹豫的评估信息。语言中智数字(LNN)作为语言术语的扩展,是通过三个独立的语言隶属函数完全,定性地传达此类评估信息的有效手段。我们的工作目的是调查几个平均算子,以便在语言中智环境下解决矿井的安全评估问题。在矿山安全评估过程中,应考虑许多影响因素,其中一些因素可能会相互影响。为此,采用了Muirhead均值(MM)运算符,因为它们是处理此类情况的强大工具。另一方面,为了减少评估人员提供的不合理数据的影响,正在考虑使用功率平均(PA)运算符。因此,结合MM和PA,提出了功率MM算子和加权功率MM算子来集合语言中智信息。同时,研究了一些关键点和特殊情况。这些运算符的优点在于,不仅可以反映任意数量输入之间的相互关系,而且可以减少不合理信息的影响。此后,基于这些算子的一种新的语言中智排序技术被开发出来,以评估矿山的安全性。此外,进行了深入讨论以显示我们方法的强大和灵活的能力。结果表明,所提出的方法在语言中智环境下成功地处理了矿山安全评估问题。

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  • 年(卷),期 -1(14),10
  • 年度 -1
  • 页码 e0224090
  • 总页数 21
  • 原文格式 PDF
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