Applicability of the fuzzy operators in the design of fuzzy logic controllers
Fuzzy Sets and Systems
A new interpolative reasoning method in sparse rule-based systems
Fuzzy Sets and Systems
A unified parameterized formulation of reasoning in fuzzy modeling and control
Fuzzy Sets and Systems
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Knowledge Representation in Fuzzy Logic
IEEE Transactions on Knowledge and Data Engineering
Parameter conditions for monotonic Takagi-Sugeno-Kang fuzzy system
Fuzzy Sets and Systems - Fuzzy systems
On the use of fuzzy inference techniques in assessment models: part I--theoretical properties
Fuzzy Optimization and Decision Making
On the use of fuzzy inference techniques in assessment models: part II: industrial applications
Fuzzy Optimization and Decision Making
On distance between fuzzy variables
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Monotone Mamdani--Assilian models under mean of maxima defuzzification
Fuzzy Sets and Systems
On the monotonicity of hierarchical sum--product fuzzy systems
Fuzzy Sets and Systems
On Fuzzy Inference System Based Failure Mode and Effect Analysis (FMEA) Methodology
SOCPAR '09 Proceedings of the 2009 International Conference of Soft Computing and Pattern Recognition
IEEE Transactions on Fuzzy Systems
A fuzzy group decision-making model with risk-taking attitudes in quality function deployment
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
A procedure ontology for advanced diagnosis of process systems
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Enhancing the Failure Mode and Effect Analysis methodology with fuzzy inference techniques
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
A fuzzy inference system-based criterion-referenced assessment model
Expert Systems with Applications: An International Journal
Fault diagnosis system based on fuzzy logic: Application to a valve actuator benchmark
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Size reduction by interpolation in fuzzy rule bases
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Similarity-based approximate reasoning: methodology and application
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A generalized concept for fuzzy rule interpolation
IEEE Transactions on Fuzzy Systems
Fuzzy interpolative reasoning via scale and move transformations
IEEE Transactions on Fuzzy Systems
Fuzzy Interpolation and Extrapolation: A Practical Approach
IEEE Transactions on Fuzzy Systems
Brief Ensuring monotonic gain characteristics in estimated models by fuzzy model structures
Automatica (Journal of IFAC)
Special issue: Hybrid approaches for approximate reasoning
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Hybrid approaches for approximate reasoning
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Computational intelligence models for image processing and information reasoning
Intelligent control for long-term ecological systems
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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In this paper, the zero-order Sugeno Fuzzy Inference System FIS that preserves the monotonicity property is studied. The sufficient conditions for the zero-order Sugeno FIS model to satisfy the monotonicity property are exploited as a set of useful governing equations to facilitate the FIS modelling process. The sufficient conditions suggest a fuzzy partition at the rule antecedent part and a monotonically-ordered rule base at the rule consequent part that can preserve the monotonicity property. The investigation focuses on the use of two Similarity Reasoning SR-based methods, i.e., Analogical Reasoning AR and Fuzzy Rule Interpolation FRI, to deduce each conclusion separately. It is shown that AR and FRI may not be a direct solution to modelling of a multi-input FIS model that fulfils the monotonicity property, owing to the difficulty in getting a set of monotonically-ordered conclusions. As such, a Non-Linear Programming NLP-based SR scheme for constructing a monotonicity-preserving multi-input FIS model is proposed. In the proposed scheme, AR or FRI is first used to predict the rule conclusion of each observation. Then, a search algorithm is adopted to look for a set of consequents with minimized root means square errors as compared with the predicted conclusions. A constraint imposed by the sufficient conditions is also included in the search process. Applicability of the proposed scheme to undertaking fuzzy Failure Mode and Effect Analysis FMEA tasks is demonstrated. The results indicate that the proposed NLP-based SR scheme is useful for preserving the monotonicity property for building a multi-input FIS model with an incomplete rule base.