This paper proposes an adaptive constraint based framework for fault detection of a complex thermal power plant system. In many complex systems, representation of precise and crisp constraints uses formal specification languages such as Object Constraint Language (OCL). Here, a constraint based neuro-fuzzy controller to tackle imprecise constrained objects is proposed. The proposed inference sy...

This paper deals with four types of point estimators based on minimization of informationtheoretic divergences between hypothetical and empirical distributions. These were introduced (i) by Liese & Vajda (2006) and independently Broniatowski & Keziou (2006), called here power superdivergence estimators, (ii) by Broniatowski & Keziou (2009), called here power subdivergence estimators, (iii) by B...

In reliability, quality control and risk analysis, fuzzy methodologies are more and more involved and inevitably introduced difficulties in seeking fuzzy functional relationship between factors. In this paper, we propose a scalar variable formation of fuzzy regression model based on the credibility measure theoretical foundation. It is expecting our scalar variable treatments on fuzzy regressio...

This paper proposes a novel design framework for semiactive nonlinear fuzzy control system that is a linear matrix inequality (LMI)-based systematic design methodology for nonlinear control of building structures employing magnetorheological (MR) dampers with multi-objective requirements. Multiple optimum linear controllers are designed in terms of LMIs such that global asymptotical stability a...

kernel density estimators are the basic tools for density estimation in non-parametric statistics.  the k-nearest neighbor kernel estimators represent a special form of kernel density estimators, in  which  the  bandwidth  is varied depending on the location of the sample points. in this paper‎, we  initially introduce the k-nearest neighbor kernel density estimator in the random left-truncatio...

Enabling information and knowledge to the right people in right time increases productivity and effectiveness of the decisions made. This article describes design for an Artificial Neural Network (ANN) based decision support system along with fuzzy user interface based on type-2 fuzzy sets. The system supports beneficiaries to select suitable course/curriculum. The major criteria for making suc...

 In this paper, estimation of signal power is considered. Methods of designing optimized and partially-optimized power estimators, based on the Wiener model, for complexvalued signals are presented. Our application is predictive received power level estimation in closed loop transmitter power control of mobile CDMA communications systems. The proposed estimators have the benefits of guaranteed...