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Physical Sciences and Mathematics Commons™
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Full-Text Articles in Physical Sciences and Mathematics
Combined Morphology And Svm-Based Fault Feature Extraction Technique Fordetection And Classification Of Transmission Line Faults, Revati Godse, Dr. Sunil Bhat
Combined Morphology And Svm-Based Fault Feature Extraction Technique Fordetection And Classification Of Transmission Line Faults, Revati Godse, Dr. Sunil Bhat
Turkish Journal of Electrical Engineering and Computer Sciences
A transmission line is the main commodity of power transmission network through which power is transmitted to the utility. These lines are often swayed by accidental breakdowns owing to different random origins. Hence, researchers try to detect and track down these failures at the earliest to avoid financial prejudice. This paper offers a new realtime mathematical morphology based approach for fault feature extraction. The morphological open-close-median filter is exploited to wrest unique fault features which are then fed as an input to support vector machine to detect and classify the short circuit faults. The acquired graphical and numerical results of …
An Automated Eye Disease Recognition System From Visual Content Of Facial Imagesusing Machine Learning Techniques, Ashrafi Akram, Rameswar Debnath
An Automated Eye Disease Recognition System From Visual Content Of Facial Imagesusing Machine Learning Techniques, Ashrafi Akram, Rameswar Debnath
Turkish Journal of Electrical Engineering and Computer Sciences
Many eye diseases like cataracts, trachoma, or corneal ulcer can cause vision problems. Progression of these eye diseases can only be prevented if they are recognized accurately at the early stage. Visually observable symptoms differ a lot among these eye diseases. However, a wide variety of symptoms is necessary to be analyzed for the accurate detection of eye diseases. In this paper, we propose a novel approach to provide an automated eye disease recognition system using visually observable symptoms applying digital image processing techniques and machine learning techniques such as deep convolution neural network (DCNN) and support vector machine (SVM). …
Modeling Compaction Parameters Using Support Vector And Decision Treeregression Algorithms, Abdurrahman Özbeyaz, Mehmet Söylemez
Modeling Compaction Parameters Using Support Vector And Decision Treeregression Algorithms, Abdurrahman Özbeyaz, Mehmet Söylemez
Turkish Journal of Electrical Engineering and Computer Sciences
Shortening the periods of compaction tests can be possible by analyzing the data obtained from previous laboratory tests with regression methods. The regression analysis applied to current data reduces the cost of experiments, saves time, and gives estimated outputs. In this study, the MLS-SVR, KB-SVR, and DTR algorithms were employed for the first time for the estimation of soil compaction parameters. The performances of these regression algorithms in estimating maximum dry unit weight (MDD) and optimum water content (OMC) were compared. Furthermore, the soil properties (fine-grained soil, sand, gravel, specific gravity, liquid limit, and plastic limit) were employed as inputs …