A Comparative Study of Multivariate Analysis for Selection and Classification Using Fuzzy Measures and Reasoning

Abstract

This study develops a set of decision-making tools to be used by the Navy, commercial and private enterprise to select and classify recruits and/or employees. As an addition to or potential replacement for the current Navy selection and classification process, this process utilizes current research in the latest decision support techniques. Multiple methods are tested using discriminate analysis, multiple criteria decision making fuzzy and evidence reasoning. The study allows decision-makers to combine both qualitative and qualitative information on a sailor's skills, competencies, and experiences to select recruits. The data from the selection process can be utilized to classify recruits using a computer-based algorithm. We focus on fuzzy MADM as the primary tool for combining multiple input attributes which may be crisp or uncertain The major scientific merit of this study is that we advance the area of decision making under uncertainty by providing a fuzzy modeling framework and computation structure.

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Document Details

Document Type
Technical Report
Publication Date
Dec 19, 2001
Accession Number
ADA397639

Entities

People

  • E. S. Lee
  • Shing I. Chang
  • Steven R. Hanna

Organizations

  • Kansas State University

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Algorithms
  • Classification
  • Computational Complexity
  • Computations
  • Computer Programs
  • Computers
  • Discriminate Analysis
  • Engineering
  • Multivariate Analysis
  • Operations Research
  • Reasoning
  • Recruits
  • Systems Engineering
  • Uncertainty

Readers

  • Artificial Intelligence
  • Psychometric Testing or Psychological Assessment.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.