This paper works on the concept of flatness and its practical application for the design of an optimal transient controller in a synchronous machine. The feedback linearization scheme of interest requires the generation of a flat output from which the feedback control law can easily be designed. Thus the computation of the flat output for reduced order model of the synchronous machine with simp...

this paper works on the concept of flatness and its practical application for the design of an optimal transient controller in a synchronous machine. the feedback linearization scheme of interest requires the generation of a flat output from which the feedback control law can easily be designed. thus the computation of the flat output for reduced order model of the synchronous machine with simp...

This paper studies the theory and modeling manner of solid oxide fuel cell (SOFC) into power network and its effect on small signal stability. The paper demonstrates the fundamental module, mathematical analysis and small signal modeling of the SOFC connected to single machine infinite bus (SMIB) system. The basic contribution of the study is to attenuate the low frequency oscillations by optim...

Stock market forecasting has attracted so many researchers and investors that ‎many studies have been done in this field. These studies have led to the ‎development of many predictive methods, the most widely used of which are ‎machine learning-based methods. In machine learning-based methods, loss ‎function has a key role in determining the model weights. In this study a new loss ‎function is ...

In view of pollution prediction modeling, the study adopts homogenous (random forest, bagging, and additive regression) and heterogeneous (voting) ensemble classifiers to predict the atmospheric concentration of Sulphur dioxide. For model validation, results were compared against widely known single base classifiers such as support vector machine, multilayer perceptron, linear regression and re...

this paper is concerned with the development of a novel classifier for automatic mass detection of mammograms, based on contourlet feature extraction in conjunction with statistical and fuzzy classifiers. in this method, mammograms are segmented into regions of interest (roi) in order to extract features including geometrical and contourlet coefficients. the extracted features benefit from...