The Liu estimator has consistently been demonstrated to be an attractive shrinkage method for reducing the effects of multicollinearity. The Poisson regression model is a well-known model in applications when the response variable consists of count data. However, it is known that multicollinearity negatively affects the variance of the maximum likelihood estimator (MLE) of the Poisson regressio...

Inverse sampling design is generally considered to be appropriate technique when the population is divided into two subpopulations, one of which contains only few units. In this paper, we derive the Horvitz-Thompson estimator for the population mean under inverse sampling designs, where subpopulation sizes are known. We then introduce an alternative unbiased estimator, corresponding to post-st...

The main problem when dealing with fuzzy data variables is that it cannot be formed by a model represents the through method of Fuzzy Least Squares Estimator (FLSE) which gives false estimates invalidity in case existence multicollinearity. To overcome this problem, Bridge Regression (FBRE) Method was relied upon to estimate linear regression triangular numbers. Moreover, detection multicolline...

This paper describes a quasi-fuzzy method of online stator-resistance estimation of an induction motor, where the resistance value is derived from stator-winding temperature estimation as a function of stator current and frequency through an approximate dynamic thermal model of the machine. The estimator has been designed and iterated by simulation study and then implemented by a digital signal...

This paper uses Kalman filter theory to design a state estimator for noisy discrete time Takagi–Sugeno (T–S) fuzzy models. One local filter is designed for each local linear model using standard Kalman filter theory. Steady state solutions can be found for each of the local filters. Then a linear combination of the local filters is used to derive a global filter. The local filters are time-inva...

the paper analyses issues leading to errors in graphic object classifiers. thedistance measures suggested in literature and used as a basis in traditional, fuzzy, andneuro-fuzzy classifiers are found to be not suitable for classification of non-stylized orfuzzy objects in which the features of classes are much more difficult to recognize becauseof significant uncertainties in their location and...

This paper proposes the design of a robust fault estimator for a class of nonlinear uncertain NCSs that ensures the fault estimation error is less than prescribed H performance level, irrespective of the uncertainties and networkinduced effects. T-S fuzzy models are firstly employed to describe the nonlinear plant. Markov processes are used to model these random network-induced effects. Suffici...

The aim of this article is propose a method to improve the direct torque control and design a Fuzzy Logic based Controller which can take necessary control action to provide the desired torque and flux of an asynchronous machine. It’s widely used in the industrial application areas due to several features such as fast torque response and less dependence on the rotor parameters. The major proble...

Process capability indices provide numerical measures on whether a process conforms to the defined manufacturing capability prerequisite. These have been successfully applied by companies to compete with and to lead high-profit markets by evaluating the quality and productivity performance. The loss-based process capability index Cpm, sometimes called the Taguchi index, was proposed to measure ...

Travel time is an important measurement used to evaluate the extent of congestion within road networks. This paper presents a new method to estimate the travel time based on an evolving fuzzy neural inference system. The input variables in the system are traffic flow data (volume, occupancy, and speed) collected from loop detectors located at points both upstream and downstream of a given link,...