This work incorporates the identification of model in functional form using curve fitting and genetic programming technique which can forecast present and future load requirement. Approximating an unknown function with sample data is an important practical problem. In order to forecast an unknown function using a finite set of sample data, a function is constructed to fit sample data points. Th...

Error bounds are developed for a class of quadratic programming problems. The absolute error between an approximate feasible solution, generated via a dual formulation, and the true optimal solution is measured. Furthermore, these error bounds involve considerably less work computationally than existing estimates.

Temperature Measurement is one of the major controlling parameter in Industries like Level, Flow, Pressure etc. One of such Temperature processes is taken in this paper and Modelling of the Process has been carried out and Transfer function of the Single Input Single Output (SISO) system. For the particular temperature process controller transfer function has been determined and control paramet...

This paper proposes a new training framework for mixed labeled and unlabeled data and evaluates it on the task of binary phonetic classification. Our training objective function combines Maximum Mutual Information (MMI) for labeled data and Maximum Likelihood (ML) for unlabeled data. Through the modified training objective, MMI estimates are smoothed with ML estimates obtained from unlabeled da...

This papers studies and compares the asymptotic bias of GMM and generalized empirical likelihood (GEL) estimators in the presence of estimated nuisance parameters. We consider cases in which the nuisance parameter is estimated from independent and identical samples. A simulation experiment is conducted for covariance structure models. Empirical likelihood offers much reduced mean and median bia...

The effect of hemolysis on several assays performed with the Hitachi 717 was quantified by relating the amount of error to the concentration of hemoglobin. Hemolysis interference was judged clinically significant when analyte concentration varied by > 10% from the initial value. Hemolysis interference was significant for alkaline phosphatase, aspartate aminotransferase, alpha-amylase, bilirubin...

This paper reports on the empirical evaluation of five machine learning algorithm such as J48, BayesNet, OneR, NB and ZeroR using ten performance criteria: accuracy, precision, recall, F-Measure, incorrectly classified instances, kappa statistic, mean absolute error, root mean squared error, relative absolute error, root relative squared error. The aim of this paper is to find out which classif...

Well designed conventional PID controllers using Ziegler-Nichols method are having large overshoot and settling time. Significant research work has been carried out to improve the performance of closed loop response with PID controller so that it can be used for real time temperature control system using SCADA(HC900 Honeywell controller). Also performance of PID controller is investigated for d...

This article deals with the tuning of the parameters for automatic generation control (AGC) of three-area interconnected power system. Areas of the power system consists of reheat thermal turbines with proportional-integral (PI) regulator. Particle swarm optimization (PSO) algorithm has been applied to optimize the regulator parameters. The effectiveness of different cost functions through PSO ...

The MEMS gyroscope zero drifts dominantly affects measurement accuracy of gyroscope. For the nonlinear problem that MEMS gyro zero drift varying with the temperature changes, the wavelet transform was performed to filter the static experiment zero drift data, then the zero drift was investigate by combing with the improved grey prediction theory. Finally a temperature compensation model based o...