Type-2 fuzzy logic to make up for the lack of a type of fuzzy logic in dealing with uncertainty, object contains uncertainty is strong; the application of type-2 fuzzy logic advantage is more obvious. In this paper, type-2s of fuzzy logic for power load time series forecasting, good results were obtained. According to the power load has strong randomness it is difficult to accurately forecast p...

This paper presents a type-2 fuzzy rule based expert system to handle uncertainty in complex problems such as portfolio selection. In a type-2 fuzzy expert system both antecedent and consequent have type-2 membership function. This research uses indirect approach fuzzy modeling, where the rules are extracted automatically by implementing a clustering approach. For this purpose, a new cluster an...

This paper aims 3-dof scara type robot manipulator using dynamic modeling. In this paper presents dynamic modeling of robot manipulator based on Lagrange Euler formulation using Mamdani based Fuzzy controller. The aim of designing fuzzy controller is to overcome the drawbacks of conventional PID controller because robot manipulators are nonlinear model so conventional PID controller cannot give...

In this paper, the idea of the neuro-fuzzy learning algorithm has been extended, by which the tuning parameters in the fuzzy rules can be learned without changing the fuzzy rule table form used in usual fuzzy applications. A new neuro-fuzzy learning algorithm in the case of the fuzzy singleton-type reasoning method has been proposed. Due to the flexibility of the fuzzy singleton-type reasoning ...

In Game theory, there are situations in which it is very difficult to characterize the private information of each player. In this case, the payoffs can be given by approximate values, represented by fuzzy numbers. Whenever there is uncertainty in the modeling of those fuzzy numbers, interval fuzzy numbers may be used. This paper introduces two approaches for the solution of interval-valued fuz...

until now single values of irr are traditionally used to estimate the time value of cash flows. since uncertainty exists in estimating cost data, the resulting decision may not be reliable. the most commonly cited drawbacks to using the internal rate of return in evaluatton of deterministic cash flow streams is the possibility of multiple conflicting internal rates of return. in this paper we p...

Since the single input rule modules connected fuzzy inference model (SIRMs model) is proposed by Yubazaki, Yi et al., many researches on the extension of the SIRMs model have been reported. Moreover, the fuzzy functional SIRMs inference model, in which the consequent parts of the functional-type SIRMs model are generalized to fuzzy function, has proposed as one of various extension SIRMs models...

In recent years, much attention has been focused on the ability of fuzzy logic to solve problems that were previously assumed difficult to solve. These include, for example, the use of fuzzy logic for control and pattern recognition. However, the application of fuzzy logic to the establishment of correlations between independent and dependent process variables, i.e. regression modeling, has rec...

In this study, we offer a general view at the area of fuzzy modeling and fuzzymodels, identify the visible development phases and elaborate on a new and promisingdirections of system modeling by introducing a concept of granular models. Granularmodels, especially granular fuzzy models constitute an important generalization of existingfuzzy models and, in contrast to the existing models, generat...