Es-Saïd Akhouayri

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Automatic classification of seismic events is of great importance due to the large amount of data received continuously. Seismic analysts classify events by visual inspection and calculation of event signal characteristics. This process is subjective and demands hard work as well as a significant amount of time and considerable experience. A reliable(More)
The aim of the present study is to investigate and explore the capability of the multilayer perceptron neural network to classify seismic signals recorded by the local seismic network of Agadir (Morocco). The problem is divided into two main steps, the feature extraction step and classification step. In the former, relevant discriminant features are(More)
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