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dc.contributor Graduate Program in Computer Engineering.
dc.contributor.advisor Alpaydın, Ethem.
dc.contributor.advisor Ertüzün, Ayşın.
dc.contributor.author Dimililer, Nazife.
dc.date.accessioned 2023-03-16T09:59:44Z
dc.date.available 2023-03-16T09:59:44Z
dc.date.issued 1995.
dc.identifier.other CMPE 1995 D59
dc.identifier.uri http://digitalarchive.boun.edu.tr/handle/123456789/12101
dc.description.abstract Earthquake Prediction is a mainly unsolved problem. A large number of different approaches have been tried and only a small number of attempts were fruitful. A few of these are explained briefly in this thesis. One of the most succesful earthquake prediction sytems in use today is the Canada-Nevada, CN, algorithm. It is discussed and contrasted to the neural networks implemented in the project. For this project the earthquake prediction problem is treated as a time senes prediction problem and neural networks that have been used for ordinary time senes prediction with some success have been applied to the problem. The data used was treated as a two dimensional time series with two variables; the magnitude of the present earthquake, and the time elapsed since the previous earthquake. The neural network architectures implemented were the" multilayer perceptron network with sigmoidal activation function, NADINE, and a mult,ilayer network with chaotic activation function. The results were not succesful because of the complex nature of input data and the earthquake generation process.
dc.format.extent 30 cm.
dc.publisher Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 1995.
dc.subject.lcsh Earthquakes.
dc.subject.lcsh Earthquake prediction.
dc.subject.lcsh Neural networks (Computer science)
dc.title Earthquake prediction using neural networks
dc.format.pages x, 92 leaves:


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