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Showing 1 to 6 of 6 for “"ANN Classifier"”.
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Fault Identification of UPFC-Compensated Transmission Lines in Complex Microgrids Using an Intelligent Relaying Scheme Based on Discrete Wavelet Transform and ANN Classifier
… extraction and artificial neuron network (ANN) for feature classification of fault currents. The main objectives are automatic detection and identification of fault type with the best accuracy, reliability, and reduced computational complexity. Furthermore, to analyze the impact of UPFC on …
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Application of Machine Learning Techniques for the Classification of Lower Back Pain in Human Body
… the Logistic Regression algorithm is the best classifier in terms of Accuracy giving 90.91% accurate results on test data followed by an Artificial Neural Network algorithm whose accuracy is 88.64%. In terms of Precision calculation, the Logistic Regression is best and the ANN Classifier is …
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An artificial neural network approach to transformer fault diagnosis
… thesis presents an artificial neural network (ANN) approach to diagnose and detect faults in oil-filled power transformers based on dissolved gas-in-oil analysis. The goal of the research is to investigate the available transformer incipient fault diagnosis methods and then develop an ANN …
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An investigation of neural computing applied to the ambulatory monitoring of the electrocardiogram
… technique based on artificial neural networks (ANNs) was selected for further research. It is shown that whilst techniques based on artificial neural networks are capable of performing the required pattern recognition task, results are presented to demonstrate that the sensitivity of the ANN …
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Embedded hardware architecture for multi-parameter physiological signal monitoring
… extraction) and an artificial neural network (ANN) classifier allows one to achieve high detection accuracy (99.18%) with moderate hardware footprint (around 44% of the FPGA resources). Furthermore, use of algorithmic and architectural optimization techniques (reduction in precision of the …
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Análisis de texturas mediante el histograma de frecuencias de elementos conexo
… the back-propagation algorithm, is the specific ANN classifier applied for the detection and recognition of textures in digital images. Finally, this architecture and the FHCE are applied to a real automatic wood inspection system. The problem that is to be solved is the detection of defects in …