With respect to multiple attribute decision making (MADM) problems in which the attribute value takes the form of intuitionistic trapezoidal fuzzy number, a new decision making analysis method is developed. Firstly, some operational laws and expected values of intuitionistic trapezoidal fuzzy numbers, and distance between two intuitionistic trapezoidal fuzzy numbers, are introduced, and the com...

Here we consider approaches to the ranking of fuzzy numbers based upon the idea of associating with a fuzzy number a scalar value, its signal/noise ratios, where the signal and the noise are defined as the middle-point and the spread of each $gamma$-cut of a fuzzy number, respectively. We use the value of a as the weight of the signal/noise ratio of each $gamma$-cut of a fuzzy number to calcula...

Direct torque control (DTC) is a new method of induction motor control. The key issue of the DTC is the strategy of selecting proper stator voltage vectors to force stator flux and developed torque within a prescribed band. Due to the nature of hysteresis control adopted in DTC, there is no difference in control action between a larger torque error and a small one. It is better to divide the to...

This paper deals with the design of a fuzzy PID Controller (FPIDC) with dynamic gain through a fuzzy scheme. The gain factor of Proportional, Integral and Derivative is varied according to process of the proposed dead time. FPIDC is modified which depends on the normalized change of error of the controlled variable (ec) and its number of fuzzy partitions. The proposed scheme is tested for a wid...

Many methods for ranking fuzzy numbers have been proposed. The existing methods for ranking generalized fuzzy numbers based on the optimistic index (α) gives different values for comparing the numbers by using different values of the optimistic index (α) and it is the shortcoming of this method. So we introduce a new defuzzification using a crisp number for ordering and comparing the fuzzy numb...

Data mining techniques can be used to discover useful patterns by exploring and analyzing data and it’s feasible to synergistically combine machine learning tools to discover fuzzy classification rules. In this paper, an adaptive neuro fuzzy network with TSK fuzzy type and an improved quantum subtractive clustering has been developed. Quantum clustering (QC) is an intuition from quantum mechani...

A comparison of different T-norms and S-norms for interval type-2 fuzzy number weights is proposed in this work. The interval type-2 fuzzy number weights are used in a neural network with an interval backpropagation learning enhanced method for weight adjustment. Results of experiments and a comparative research between traditional neural networks and the neural network with interval type-2 fuz...

This paper deals with using fuzzy logic to minimize uncertainty effects in surveillance. It studies the conception of an efficient fuzzy expert system that had two characteristics: generic and robust to uncertainties. Analyzing distance between variables optimal and real values is the main idea of the research. Fuzzy inference system decides, then, about significant variables state: normal or a...

— Several Multi-Criteria Decision Making (MCDM) methods involve pairwise comparisons to obtain the preferences of decision makers (DMs). This paper proposes a fuzzy group prioritization method for deriving group priorities/weights from fuzzy pairwise comparison matrices. The proposed method extends the Fuzzy Preferences Programming Method (FPP) by considering the different importance weights of...

The paper proposes a new approach for tackling the uncertainty and imprecision of the reasoning process while using decision support tools during prenegotiations. The pre-negotiation problem is regarded as decision making under uncertainty, based on multiple criteria of quantitative and qualitative nature, where the imprecise decision-maker’s judgments are represented as fuzzy numbers. A new fu...