A special fuzzy modeling method for developing multi-variable fuzzy models on the basis of measured input and output data is presented. Representing the crucial point in fuzzy modeling, the fuzzy model identiication procedure is carried out by applying a special clustering method, the fuzzy c-elliptotypes method, providing the parameters of the fuzzy model. To enhance the eeciency of the fuzzy ...

the basic models of data envelopment analysis (dea) are designed in such a way that the values of input and output indicators should be identified and known in them. in other words, these models are not used to consider inaccurate, interval, fuzzy, judgment data. in this paper, the aim is to not only review the past researches about the efficiency of the units by interval data and represent the...

the aim of this research is the assessment of the relation between rainfall and large scale synoptically patterns at khorasan razavi province. in this study, using adaptive neuro fuzzy inference system, the rainfall estimation has been done from april to june in the area under study. spring rainfall data including the information of 38 synoptic, climatologic and rain gauge stations from 1970 to...

Klaus S hmid and Volker Krebs Universität Karlsruhe (TH), Institut für Regelungsund Steuerungssysteme Kaiserstr. 12, D-76131 Karlsruhe, Germany e-mail: {s hmid, krebs} irs.ete .uni-karlsruhe.de Abstra t. A dynami fuzzy system is a mapping of fuzzy input values onto a fuzzy output value with a feedba k to the input. In this paper, we present a new rule-based inferen e method that an be used in d...

In the cases of control systems where physical mechanisms are not well known due to high complexity and nonlinearity, a fuzzy relational model may be useful. In this paper, we propose a recursive parameter tuning algorithm for the identification of fuzzy relational model for an unknown dynamic system. Furthermore, using the fact that a dynamic system is represented by the relational strength be...

In this paper, Two Mamdani type fuzzy models (four inputs–one output and two inputs–one output) were developed to test the hypothesis that high job demands and low job control (job strain) are associated with elevated free cortisol levels early in the working day and with reduced variability across the day and to evaluate the contribution of anger expression to this pattern. The models were der...

A distributed, scalable and flexible fuzzy logic controller (FLC)without increasing additional hardware cost by fuzzy accuracy factor is proposed. In order to improve fuzzy logic operation speed, multi-input/ multi-output (MIMO) fuzzy system is decomposed into several independent two-input/single-output (TISO) subsystems in parallel. The decomposed TISO FLC can deal with scalable requirements i...

introduction: studies have indicated a global high prevalence of hospital malnutrition on admission and during hospitalization. clinical nutritional risk screen (cnrs) is a way to identify malnutrition and manage nutritional interventions. several traditional and non-computer based tools have been suggested for screening nutritional risk levels. the present study was an attempt to employ a comp...

This paper proposs a systematic methodology of fuzzy logic modeling as a generic tool for modeling of complex systems. The methodology conveys three distinct features: 1) a unified parameterized reasoning formulation; 2) an improved fuzzy clustering algorithm; and 3) an efficient strategy of selecting significant system inputs and their membership functions. The reasoning mechanism introduces f...

This paper deals with the simplest fuzzy PI controllers under various defuzzification methods. The various simplest fuzzy PI controllers consist of two triangular input fuzzy sets and three triangular output fuzzy sets on the universe of discourse of input and output variables, respectively, linear control rules, intersection T-norm, Lukasiewicz and Zadeh OR T-conorms, and any valid inference m...