Title :
Study of seismic activity in Central Asia applying a parallel distributed paradigm
Author :
Lin, Frank C. ; Panikkar, Indira
Author_Institution :
Dept. of Math & Comput. Sci., Maryland Univ., Princess Anne, MD, USA
Abstract :
Historical data of time, location and magnitude of earthquakes in Central Asia from 25 A.D. to the present are inputted into a neural network and trained using the backpropagation paradigm. The resulting network is utilized to make predictions
Keywords :
backpropagation; earthquakes; geophysics computing; neural nets; seismology; AD 0025 to 1995; Central Asia; China; backpropagation; earthquake prediction; forecasting; geophysical computing; location; magnitude; neural net; neural network; parallel distributed paradigm; prediction; seismic activity; seismicity; seismology; training; Asia; Backpropagation; Computer science; Earthquakes; Mathematical model; Neural networks; Predictive models; Seismology; Solids; Technology forecasting;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 1995. IGARSS '95. 'Quantitative Remote Sensing for Science and Applications', International
Conference_Location :
Firenze
Print_ISBN :
0-7803-2567-2
DOI :
10.1109/IGARSS.1995.524145
