ON MONOTONIC SUFFICIENT CONDITIONS OF FUZZY INFERENCE SYSTEMS AND THEIR APPLICATIONS

DOI10.1142/S0218488511007210zbMath1237.68225DBLPjournals/ijufks/TayL11WikidataQ58219264 ScholiaQ58219264MaRDI QIDQ2886918

Kai Meng Tay, Chee Peng Lim

Publication date: 14 May 2012

Published in: International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems (Search for Journal in Brave)

zbMATH Keywords

sufficient conditionsfuzzy controllerrisk assessmentmonotonicity propertyfailure mode and effect analysis (FMEA)sub-additivity property

Mathematics Subject Classification ID

Reasoning under uncertainty in the context of artificial intelligence (68T37)

Cites Work

• Monotone Mamdani-Assilian models under mean of maxima defuzzification
• Analysis of interpretability-accuracy tradeoff of fuzzy systems by multiobjective fuzzy genetics-based machine learning
• On the use of fuzzy inference techniques in assessment models. I: Theoretical properties
• On the use of fuzzy inference techniques in assessment models. II: Industrial applications
• Parameter conditions for monotonic Takagi-Sugeno-Kang fuzzy system
• Ensuring monotonic gain characteristics in estimated models by fuzzy model structures
• On the monotonicity of hierarchical sum-product fuzzy systems
• The Concept of Elasticity in Economics
• Monotone control systems

This page was built for publication: ON MONOTONIC SUFFICIENT CONDITIONS OF FUZZY INFERENCE SYSTEMS AND THEIR APPLICATIONS