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Advantage matrix: two novel multi-attribute decision-making methods and their applications.

Bin Yu1,2, Zeshui Xu1

  • 1Business School, Sichuan University, Chengdu, 610064 Sichuan People's Republic of China.

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|January 24, 2022
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Summary
This summary is machine-generated.

This study introduces new methods for analyzing object relationships in information systems using an advantage matrix. These methods enhance understanding of object advantages and correlations, leading to improved algorithms.

Keywords:
Advantage (disadvantage) correlation approximation operatorAdvantage (disadvantage) neighborhood approximation operatorAdvantage (neighborhoodAdvantage matrixDecision-makingcorrelation)

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Area of Science:

  • Information Science
  • Computer Science
  • Data Analysis

Background:

  • Information systems often involve complex relationships between objects.
  • Evaluating these relationships is crucial for effective data analysis and system design.

Purpose of the Study:

  • To develop novel methods for quantifying object advantages and relationships within information systems.
  • To introduce new approximation operators and degree measures for enhanced data analysis.

Main Methods:

  • Establishing an advantage matrix by comparing object attributes.
  • Defining advantage (disadvantage) neighborhood and correlation approximation operators.
  • Proposing neighborhood and correlation degree measures based on the advantage matrix.

Main Results:

  • The accumulation of the advantage matrix yields a proposed 'advantage degree'.
  • New neighborhood and correlation approximation operators and their corresponding degrees were defined and studied.
  • The relationships between these new measures were investigated.

Conclusions:

  • The proposed methods and derived degrees offer a valuable framework for analyzing object relationships.
  • New algorithms based on these degrees demonstrate effectiveness and robustness in practical applications.