TY - CONF

T1 - A Systematic Approach to the Optimal Design of Feed Forward Neural Networks Applied to Log-Synthesis

AU - Fruhwirth, Rudolf Konrad

AU - Steinlechner, Sepp Peter

PY - 2004

Y1 - 2004

N2 - G001 A SYSTEMATIC APPROACH TO THE OPTIMAL DESIGN OF FEED FORWARD NEURAL NETWORKS APPLIED TO LOG-SYNTHESIS Abstract 1 Neural networks are increasingly used in geophysical applications. Optimizing neural networks is still a matter of experience and trial and error where network initialization and network size are the most challenging issues. We expanded conventional learning rules to a completely forward connected network including input neurons for automatic normalization of the data. In addition we developed a method for the network initialization based on the statistical properties of the input and output data generating an initial network state that ascertains a fast

AB - G001 A SYSTEMATIC APPROACH TO THE OPTIMAL DESIGN OF FEED FORWARD NEURAL NETWORKS APPLIED TO LOG-SYNTHESIS Abstract 1 Neural networks are increasingly used in geophysical applications. Optimizing neural networks is still a matter of experience and trial and error where network initialization and network size are the most challenging issues. We expanded conventional learning rules to a completely forward connected network including input neurons for automatic normalization of the data. In addition we developed a method for the network initialization based on the statistical properties of the input and output data generating an initial network state that ascertains a fast

M3 - Paper

T2 - 66th EAGE Conference & Exhibition 2004

Y2 - 7 June 2004 through 10 June 2004

ER -