Predicting the Earthquake Magnitude Using the Multilayer Perceptron Neural Network with Two Hidden Layers

سال انتشار: 1394
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 605

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شناسه ملی سند علمی:

JR_CEJ-2-1_001

تاریخ نمایه سازی: 16 شهریور 1395

چکیده مقاله:

Because of the major disadvantages of previous methods for calculating the magnitude of the earthquakes, the neural network as a new method is examined. In this paper a kind of neural network named Multilayer Perceptron (MLP) is used to predict magnitude of earthquakes. MLP neural network consist of three main layers; input layer, hidden layer and output layer. Since the best network configurations such as the best number of hidden nodes and the most appropriate training method cannot be determined in advance, and also, overtraining is possible, 128 models of network are evaluated to determine the best prediction model. By comparing the results of the current method with the real data, it can be concluded that MLP neural network has high ability in predicting the magnitude of earthquakes and it’s a very good choice for this purpose

نویسندگان

Jamal Mahmoudi

PhD Candidate, Structural Engineering Research Center, International Institute of Earthquake Engineering and Seismology, Tehran, Iran

Mohammad Ali Arjomand

Assistant Professor, Faculty of Civil Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran

Masoud Rezaei

Faculty of Earthquake Engineering, Road-Building and Housing Research Center, Tehran, Iran

Mohammad Hossein Mohammadi

Faculty of Civil Engineering, Kharazmi University, Tehran, Iran