A Study on Quadri-Partitioned Interval-Valued Pythagorean Neutrosophic Fuzzy MCDM

Q1 Decision Sciences

Annals of Data Science Pub Date : 2025-06-06 DOI:10.1007/s40745-025-00621-z

Manajit Roy, Bhimraj Basumatary, Binod Chandra Tripathy

引用次数: 0

Abstract

We present two methods for solving multicriteria fuzzy decision-making based on a Quadri partitioned interval-valued Pythagorean neutrosophic set. Firstly, we deduce the alternatives with different weights using averaging and geometric operators, and then we use the accuracy function or score function for choosing the optimal solution. Finally, a practical example is provided to illustrate the practicality and effectiveness of the proposed approach.

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四分区间值毕达哥拉斯中性模糊MCDM的研究

提出了两种基于四次划分区间值毕达哥拉斯中性集的多准则模糊决策求解方法。首先利用平均算子和几何算子推导出不同权重的备选方案，然后利用精度函数或分数函数选择最优解。最后，通过一个实例说明了所提方法的实用性和有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Annals of Data Science Decision Sciences-Statistics, Probability and Uncertainty

CiteScore

6.50

自引率

0.00%

发文量

期刊介绍： Annals of Data Science (ADS) publishes cutting-edge research findings, experimental results and case studies of data science. Although Data Science is regarded as an interdisciplinary field of using mathematics, statistics, databases, data mining, high-performance computing, knowledge management and virtualization to discover knowledge from Big Data, it should have its own scientific contents, such as axioms, laws and rules, which are fundamentally important for experts in different fields to explore their own interests from Big Data. ADS encourages contributors to address such challenging problems at this exchange platform. At present, how to discover knowledge from heterogeneous data under Big Data environment needs to be addressed. ADS is a series of volumes edited by either the editorial office or guest editors. Guest editors will be responsible for call-for-papers and the review process for high-quality contributions in their volumes.