This paper deals with uncertain parabolic fluid flow problem where the uncertainty occurs due to the initial conditions and parameters involved in the system. Uncertain values are considered as fuzzy and these are handled through a recently developed method. Here the concepts of fuzzy numbers are combined with Finite Difference Method (FDM) and then Fuzzy Finite Difference Method (FFDM) has bee...

Abstract: One of control methods for underactuated manipulators is known as a switching control which selects a partiallystable controller using a prespecified switching rule. A switching computed torque control with a fuzzy energy region method was proposed. In this approach, some partly stable controllers are designed by the computed torque method, and a switching rule is based on fuzzy energ...

this paper presents a delay compensator fuzzy control for trajectory tracking of omni-directional mobile robots. fuzzy logic control (flc) of the robots is a suitable strategy for dealing with model uncertainties, nonlinearities and disturbances.  on the other hand, in many robotic applications such as mobile robots, delay phenomenon is able to substantially deteriorate the behavior of system's...

The coordination of two-echelons supply chain by buyback contract under the imperfect product quality and fuzzy demand environment is investigated in this paper. The mathematical models are built based on credibility theory, and the optimal parameters of buyback contract are obtained. In addition, the influence of the imperfect product rate on the parameters of buyback contract is analyzed. Fin...

1. UNCERTAINTY: ONE MUST FIGHT, BUT ONE CAN’T WIN 9 1.1. To recognize a situation 9 1.2 Predicting tomorrow 11 1.3 An expert and his cognitive activity 12 1.4 Statistics and quasi-statistics 13 2. FUZZY SETS COME TO THE AID 14 2.1 The Carrier 14 2.2 Fuzzy set 15 2.3 The Function of Belonging 15 2.4 The Linguistic Variable 15 2.5 Operations on fuzzy sub-sets 16 2.6 Fuzzy numbers and operations o...

Fuzzy linear regression models are used to obtain an appropriate linear relation between a dependent variable and several independent variables in a fuzzy environment. Several methods for evaluating fuzzy coefficients in linear regression models have been proposed. The first attempts at estimating the parameters of a fuzzy regression model used mathematical programming methods. In this the...

In this paper, a fuzzy production inventory model with resalable returns has been analysed in an imprecise and uncertain environment by considering the cost and revenue parameters as trapezoidal fuzzy numbers. The main objective is to determine the optimal fuzzy production lotsize which maximizes the expected profit where the products leftout at the end of the period are salvaged and demands wh...

This paper presents the application of neuro-fuzzy approach for modelling tool life, torque and thrust force in drilling operation for set of given process parameters, namely cutting speed, feed rate and drill diameter. The proposed approach uses a hybrid-learning algorithm i.e., combination of the back-propagation gradient descent method and least squares method, to identify premise and conseq...

In general, the conventional techniques like loop impedance and nodal admittance methods are used to find the parameters of SEIG for finding performance under various conditions. In these approaches, long mathematical calculations are involved. With the recent development, ANN and fuzzy logic are used for finding various parameters for different values of machine parameters. By finding these pa...

This paper proposes the procedure to find out the total average cost in terms of crisp values for /M/1/BD/MV with fuzzy parameters. In which arrival rate, service rate, batch size, setup, vacation, breakdown, repair rates, and the start up ,build up, holding, setup, dormant, breakdown costs and cost for busy and vacation periods are all considered as trapezoidal fuzzy numbers. As ranking techni...