Split shear-wave analysis using an artificial neural network ?
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Artificial neural networks (ANNs) are simple models that attempt to simulate the operation of neurons in the brain. Although ANNs are relatively new in seismology, their origins can be traced back to the 1940s when psychologists began developing models of human learning. One of the most exciting developments in ANNs was the advent of the Perceptron, the idea that a network of elemental processors arrayed in a marmer
reminiscent of biological neural networks might be able to learn how to recognize and classify patterns in an autonomous manner. However, in 1969, Marvin Minsky, one of the founding fathers of artificial intelligence, proved mathematically that perceptrons
were incapable of solving many simpIe problems.
[1] Michael E. Murat,et al. AUTOMATED FIRST ARRIVAL PICKING: A NEURAL NETWORK APPROACH1 , 1992 .
[2] Michael D. McCormack,et al. FIRST-BREAK REFRACTION EVENT PICKING AND SEISMIC DATA TRACE EDITING USING NEURAL NETWORKS , 1993 .
[3] Mary M. Poulton,et al. Location of subsurface targets in geophysical data using neural networks , 1992 .