Application of Soft Computing and Intelligent Methods in Geophysics
This book provides a practical guide to applying soft-computing methods to interpret geophysical data. It discusses the design of neural networks with Matlab for geophysical data, as well as fuzzy logic and neuro-fuzzy concepts and their applications. In addition, it describes genetic algorithms for the automatic and/or intelligent processing and interpretation of geophysical data.
This book provides a practical guide to applying soft-computing methods to interpret geophysical data. It discusses the design of neural networks with Matlab for geophysical data, as well as fuzzy logic and neuro-fuzzy concepts and their applications. In addition, it describes genetic algorithms for the automatic and/or intelligent processing and interpretation of geophysical data.
Autres titres de la collection: Springer Geophysics
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Laboratory Characterization of Shale
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Advances in Modeling and Interpretation in Near Surface Geophysics
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Geodetic Time Series Analysis in Earth Sciences
Springer EN, 2019
978-3-030-21717-4
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Tsunami Generation and Propagation
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Geophysical Methods for Cultural Heritage Management
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Fundamentals of Petrophysics
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Fractured Vuggy Carbonate Reservoir Simulation
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Seismic Forward Modeling of Fractures and Fractured Medium Inversion
Springer EN, 2018
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Principles and Applications of Well Logging
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Recent Advances in Rock Magnetism, Environmental Magnetism and Paleomagnetism
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Springer EN, 2018
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Physics of Petroleum Reservoirs
Springer ENPetroleum Industry Press, 2018
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