Ehab F. El-Saadany

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This paper presents a novel approach for the classification of power quality disturbances. The approach is based on inductive learning by using decision trees. The wavelet transform is utilized to produce representative feature vectors that can accurately capture the unique and salient characteristics of each disturbance. In the training phase, a decision(More)
This paper presents a new technique for predicting wind speed and direction. This technique is based on using a linear time-series-based model relating the predicted interval to its corresponding oneand two-year old data. The accuracy of the model for predicting wind speeds and directions up to 24 h ahead have been investigated using two sets of data(More)
Recently, integration of distributed generation (DG) in distribution systems has increased to high penetration levels. The impact of DGunits on the voltage stabilitymargins has become significant. Optimization techniques are tools which can be used to locate and size the DG units in the system, so as to utilize these units optimally within certain limits(More)
This note focuses on extracting and analysing prostate texture features from trans-rectal ultrasound (TRUS) images for tissue characterization. One of the principal contributions of this investigation is the use of the information of the images' frequency domain features and spatial domain features to attain a more accurate diagnosis. Each image is divided(More)
This paper proposes a novel online coordination method for the charging of plug-in electric vehicles (PEVs) in smart distribution networks. The goal of the proposed method is to optimally charge the PEVs in order to maximize the PEV owners’ satisfaction and to minimize system operating costs without violating power system constraints. Unlike the solutions(More)