GNGTS 2023 - Atti del 41° Convegno Nazionale

Session 3.3 ______ ___ GNGTS 2023 References Aleardi M. and Mazzotti A.; 2016: 1D elastic full-waveform inversion and uncertainty estimation by means of a hybrid genetic algorithm-Gibbs sampler approach. Geophysical Prospecting, 65, doi: 10.1111/1365-2478.12397. Aleardi M., Vinciguerra A. and Hojat A.; 2021: A convolutional neural network approach to electrical resistivity tomography. Journal of Applied Geophysics, 193, doi: 10.1016/j.jappgeo.2021.104434. Haykin S.S.; 2009: Neural Networks and Learning Machines. Third Edition. Pearson Education, Upper Saddle River, NJ, 906 pp. Karaoulis M., Tsourlos P.I., Werkema D. and Minsley B.; 2013: IP4DI: A software for time-lapse 2D/3D DC-resistivity and induced polarization tomography. Computers & Geosciences, 54, 164-170, doi: 10.1016/j.cageo.2013.01.008. Moseley B., Nissen-Meyer T. and Markham A.; 2020: Deep learning for fast simulation of seismic waves in complex media. Solid Earth, 11, 1527-1549, doi: 10.5194/se-11-1527-2020. Pohlheim H.; 2006: GEATbx: Genetic and Evolutionary Algorithm Toolbox for use with Matlab. doi: 10.1007/978-3-642-57137-4_6. Vinciguerra A., Aleardi M., Hojat A., Loke M.H. and Stucchi E.; 2021: Discrete cosine transform for parameter space reduction in Bayesian electrical resistivity tomography. Geophysical Prospecting, 70, 193-209, doi: 10.1111/1365-2478.13148. Fabio Macelloni, fabio.macelloni@phd.unipi.it