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We introduce a design procedure for fuzzy systems using the concept of information granulation and genetic optimization.
Firstly, a design procedure for fuzzy descriptor observer is proposed to estimate the states of the fuzzy system and unknown sensor faults.
A general sensitivity analysis procedure for fuzzy rule-based systems is proposed and then implemented, to identify the most important supplier capabilities and willingness criteria and to formulate better supplier development strategies.
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This paper presents the extension and implementation of the method of fuzzy clustering of fuzzy data proposed by Yang and Liu [Yang, M.-S. and Liu, H-H, H-H,. Fuzzy clustering procedures for conical fuzzy vector data. Fuzzy Sets and Systems, 1999 189-200.].
This paper presents a design procedure for Mamdani fuzzy logic controller including rule base minimisation.
Based on the developed model, the design procedure for the fuzzy logic urea dosage controller was well addressed.
The proposed scheme lays out a unique adaptive procedure for designing fuzzy controllers through iterative learning process.
Moreover, Chalco-Cano et al. discussed the formulation and procedure for solving fuzzy differential equations via a differential inclusion and gave several examples showing the corrected and incorrect procedure for solving differential equations in [8].
Then, this study developed an identification procedure for λ-fuzzy measures using genetic algorithms.
Numerical procedures for solving fuzzy integral equations of the second kind, based on the method of successive approximations and other iterative techniques, have been investigated in [5 9].
Following this, the procedure for the proposed fuzzy rules is described in Figure 5; these fuzzy rules allow the analyst to characterize the presence of motion and/or noise in the sample in order to determine which procedure to utilize during the image processing.
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