An extended fuzzy measure on competitiveness correlation based on WCY 2011

  • Authors:
  • Yu-Chien Ko;Hamido Fujita;Gwo-Hshiung Tzeng

  • Affiliations:
  • Department of Information Management, Chung Hua University, 707, Sec. 2 Wufu Road, Hsinchu 30012, Taiwan;Software and Information Science, Iwate Prefectural University, Takizawa, Japan;Graduate Institute of Project Management, Kainan University, No. 1 Kainan Road, Luchu, Taoyuan County 338, Taiwan and Institute of Management of Technology, National Chiao Tung University, Ta-Hsuc ...

  • Venue:
  • Knowledge-Based Systems
  • Year:
  • 2013

Quantified Score

Hi-index 0.00

Visualization

Abstract

The fuzzy measure can highlight important information in analyzing component features, patterns, and trends. However, fuzzy densities and interaction effects are usually unknown or uncertain for implications thus making the fuzzy measure limited in applications. This research proposes an extended fuzzy measure to derive the conditional fuzzy densities from dominance-based rough set approach (DRSA), multiply preferences and the derived densities into utilities, fulfill fuzzy measure identification, and empower the fuzzy measure to aggregate utilities. For illustration, the extended fuzzy measure is applied on World Competitiveness Yearbook 2011 to imply policy-making information for Greece, Italy, Portugal, and Spain.