Titlebook: Geophysical Applications of Artificial Neural Networks and Fuzzy Logic; William A. Sandham,Miles Leggett Book 2003 Springer Science+Busine

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Elektrische Me?ger?te und Me?verfahren in the workload of an interpreter. An automatic tracker is described in this chapter, based on artificial neural networks (ANNs), which enables horizons to be tracked in three dimensions with less input from an interpreter compared to most commercial automatic trackers. More time can therefore be s

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https://doi.org/10.1007/978-3-662-25881-1 Pre-processing steps include envelope processing, thresholding, peak detection, and compression in time. Each peak represents a single seismic wavelet, and each pre-processed data item corresponds to one neuron in the Hopfield network. The constraint conditions for detecting seismic horizons are us

HACK

,Direkt wirkende elektrische Me?werke,ptive linear combiner (ALC), in order to refine the results of deconvolution. For example, the conventional method of designing a shaping filter for a minimum-delay wavelet, requires the computation of a fixed filter by the method of least-squares. An alternative approach, considered in this chapter

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https://doi.org/10.1007/978-3-322-99133-1layer is equal to the number of recorded samples. During training, the global minimum of the energy function is determined using a decimal-encoded genetic algorithm. It is necessary to use weights and thresholds of neurons as a gene group. To determine the weights and thresholds corresponding to the

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