FUSION OF MULTI-DIMENSIONAL POSSIBILISTIC INFORMATION VIA POSSIBILISTIC LINEAR PROGRAMMING

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概要

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• In this paper, multi-source possibilistic information is represented by a set of possibilistic constraints to characterize decision variables from different information aspects. Possibilistic linear programming is used to integrate multi-source possibilistic information into the upper and the lower possibility distributions of decision vector.

著者

• Guo P

  Kagawa University

• TANAKA Hideo

  Toyohashi Sozo College

• GUO Peijun

  Kagawa University

• Entani Tomoe

  Osaka Prefecture University

関連論文

• FUSION OF MULTI-DIMENSIONAL POSSIBILISTIC INFORMATION VIA POSSIBILISTIC LINEAR PROGRAMMING
• Identification of Upper and Lower Possibility Distributions with Rough Sets (第17回ファジィシステムシンポジウム--科学技術と自然の調和を目指して)

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