In this paper we extend the classical Lyapunov synthesis method to the domain of computing with words. This new approach is used to design fuzzy controllers. Assuming minimal knowledge about the plant to be controlled, the proposed method enables us to systematically derive the fuzzy rules that constitute the rule base of the controller. We demonstrate the approach by designing Mamdani-type and...

In regression problems, the use of TSK fuzzy systems is widely extended due to the precision of the obtained models. Moreover, the use of simple linear TSK models is a good choice in many real problems due to the easy understanding of the relationship between the output and input variables. In this paper we present FRULER, a new genetic fuzzy system for automatically learning accurate and simpl...

Case-based reasoning is a recognized paradigm and has been explored in both applied and methodological directions. In the several phases of CBR, the adaptation phase is certainly the most problematic whereas the most characteristic and interesting phase. We propose to view this task through a fuzzy analogical scheme. The adaptation is realized by focusing on the relation existing between the pr...

This paper uses a methodology based in fuzzy sets theory in order to describe the interaction between the prey, Aphis glycines (Hemiptera: Aphididae) the soybean aphid, and its predator, Orius insidiosus (Hemiptera: Anthocoridae). Economic thresholds were already developed for this pest. The aim of this investigation was to develop a simple and specific methodology by fuzzy rule-based system to...

ranking fuzzy numbers plays a very important role in decision making and some other fuzzy application systems. many different methods have been proposed to deal with ranking fuzzy numbers. constructing ranking indexes based on the centroid of fuzzy numbers is an important case. but some weaknesses are found in these indexes. the purpose of this paper is to give a new ranking index to rank vario...

kim and bishu (fuzzy sets and systems 100 (1998) 343-352) proposeda modification of fuzzy linear regression analysis. their modificationis based on a criterion of minimizing the difference of the fuzzy membershipvalues between the observed and estimated fuzzy numbers. we show that theirmethod often does not find acceptable fuzzy linear regression coefficients andto overcome this shortcoming, pr...

This paper pro oses a neural fuzzy connection admission control NFCAC) scheme, which combines of the neural-net, t o solve the connection admission control (CAC) problems in ATM networks. Recently, fuzzy logic systems have been successfully applied t o deal with the traffic control related probleims and provided a robust mathematical framework for dealing with "real-world" imprecision; multi-la...

This paper presents a new approach to robust beamforming based on fuzzy logic theory that is suitable for both point and scattered sources. The presented technique is based on the optimum beamformer and makes it robust to an imperfect estimate of the direction of arrival (DOA) even when powerful interferences are within the uncertainty range of the desired source. This robust approach solves th...

Fuzzy mining approaches have recently been discussed for deriving fuzzy knowledge. Since items may have their own characteristics, different minimum supports and membership functions may be specified for different items. In the past, we proposed a genetic-fuzzy data-mining algorithm for extracting minimum supports and membership functions for items from quantitative transactions. In that paper,...

Fuzzy Rule-Based Systems have been succesfully applied to pattern classification problems. In this type of classification systems, the classical Fuzzy Reasoning Method (FRM) classifies anew example with the consequent of the rule with the greatest degree of association. By using this reasoning method, we lose the information provided by the other rules with different linguistic labels which als...