WeChat Mini Program
Old Version Features

Multi-attribute Decision-Making Using (p, Q)-Rung Orthopair Fuzzy Hamacher Interactive Aggregation Operators

Granular Computing(2024)

University of Management and Technology

Cited 2|Views1
Abstract
Compared to Fermatean fuzzy sets, Pythagorean fuzzy sets, and intuitionistic fuzzy sets, (p, q)-rung orthopair fuzzy sets ((p, q)-ROFSs) can display membership grades over a wider range, allowing them to present more confusing circumstances. This article elaborates the use of (p, q)-ROFS in engineering design for material selection. Material selection is a crucial part of engineering because it satisfies all of the object’s functional requirements. The design process’s crucial and time-consuming phase of material selection. The output, profitability, and reputation of a manufacturer can suffer from the choice of the incorrect material(s). An essential tool in the engineering design process for handling the complexity of material selection is multi-attribute decision-making (MADM). However, the outcomes of using the current MADM approaches are frequently inconsistent. To solve these issues, a novel aggregation method based on the truthness and falsity indices of (p, q)-ROFS is suggested for material selection in engineering design. We present (p, q)-rung orthopair fuzzy Hamacher interactive aggregation operators (AOs) that take advantage of (p, q)-ROFS and smooth approximation with interactive Hamacher operations. Based on the indicated AOs, in engineering design, a trustworthy MADM method is advised for material selection (MS). The main contributions of this article are as follows: (1) The aggregation operators for (p, q)-rung orthopair fuzzy numbers and their attributes have been studied using Hamacher norms. (2) MADM is established under (p, q)-rung orthopair fuzzy sets. A step-by-step explanation of the proposed method is given using an algorithm. (3) The developed method is then applied as a case study in the selection of materials for cryogenic storage tanks. (4) The results have been contrasted with the rankings obtained by several currently employed techniques. The authenticity analysis and comparison analysis are also intended to talk about the reliability and sanity of the best choice.
More
Translated text
Key words
(p,q)-ROFS,Hamacher interactive operations,Aggregation operators,MADM
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined