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This paper proposes an intellectual classification system to recognize normal and abnormal MRI brain images. Nowadays, decision and treatment of brain tumors is based on symptoms and radiological appearance. Magnetic resonance imaging (MRI) is a most important controlled tool for the anatomical judgment of tumors in brain. In the present investigation, various techniques were used for the classification...
This paper proposes the neuro-fuzzy classification model to perform the supervised classification of the data. In the proposed classification model, fuzzy membership matrix is formed by using Gaussian membership function. Membership matrix contains the membership of each feature value to the given classes. This membership matrix is given as an input to the artificial neural network and membership...
In this study, we introduces a classification approach using Multi-Layer Perceptron (MLP)with Back-Propagation learning algorithm and a feature selection algorithm along with biomedical test values to diagnose heart disease. Clinical diagnosis is done mostly by doctor's expertise and experience. But still cases are reported of wrong diagnosis and treatment. Patients are asked to take number of tests...
This paper details a new procedure in the detection module of a general framework to detect and identify abnormalities which may be due to non-technical losses (NTL) in power utilities. Fraud detection techniques have been widely used in other businesses including credit card, telecommunications and insurance companies. However, there is very limited reporting on fraud detection in power utilities...
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