Computing with words for hierarchical decision making applied to evaluating a weapon system

  • Authors:

  • Dongrui Wu;Jerry M. Mendel

  • Affiliations:

  • Inst. for Creative Techn. and the Signal Analysis and Interpretation Lab., Viterbi School of Eng., Univ. of Southern Calif., Los Angeles, CA and Signal and Image Proc. Inst., Ming Hsieh Dept. of E ...;Signal and Image Processing Institute, Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, CA

  • Venue:
  • IEEE Transactions on Fuzzy Systems - Special section on computing with words
  • Year:
  • 2010

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Abstract

The perceptual computer (Per-C) is an architecture that makes subjective judgments by computing with words (CWWs). This paper applies the Per-C to hierarchical decision making, which means decision making based on comparing the performance of competing alternatives, where each alternative is first evaluated based on hierarchical criteria and subcriteria, and then, these alternatives are compared to arrive at either a single winner or a subset of winners. What can make this challenging is that the inputs to the subcriteria and criteria can be numbers, intervals, type-1 fuzzy sets, or even words modeled by interval type-2 fuzzy sets. Novel weighted averages are proposed in this paper as a CWW engine in the Per-C to aggregate these diverse inputs. A missile-evaluation problem is used to illustrate it. The main advantages of our approaches are that diverse inputs can be aggregated, and uncertainties associated with these inputs can be preserved and are propagated into the final evaluation.