Aquifer Parameter Estimation Using Genetic Algorithms and Neural Networks

Inverse modeling of leakage through a rockfill dam foundation during its construction stage using transient flow model, neural network and genetic algorithm

“…Lingireddy, 1998;Coppola et al, 2003;Garcia and Shigidi, 2006). There are many kinds of ANN models, among which the back propagation neural network (BPNN) model is most widely used (Neaupane and Achet, 2004).…”

“…As a fact that the hydraulic head can be obtained in the field relatively easier and cheaper than other observations, most of the inverse models rely only on the measurements of hydraulic head (e.g. Lingireddy, 1998;Karpouzos et al, 2001;Garcia and Shigidi, 2006;Chang et al, 2008;Virbulis et al, 2013), and this treatment may make the inverse solution plagued with the non-uniqueness problem (Dietrich and Newsam, 1990;Jing et al, 2007). A better strategy is to use multiple types of observations (e.g.…”

Neural Network Based Automated Interpretation Algorithm for Combined Geophysical Soundings in Coastal Zones

“…ANN had been widely used in various areas of geophysics, such as crossequalization of seismic time-lapse surveys (Ibrahim et al, 2002) identification of seismic crew noise (Buffenmyer et al, 2000), identification of seismic arrival types , seismic attribute calibration (Johnston, 1993), seismic inversion (Poulton et al, 1992., Roth and Tarantola, 1994., Boadu, 1998, fractured reservoir characterization (Ouenes, 2000), first arrival or arrival picking (Murat and Rudman, 1992;Mc Cormack et al, 1993;Mac Bath, 1995, 1997), seismic event classification (Dystart and Pulli, 1990), earthquake prediction (Feng et al, 1997), discrimination of genuine from spurious seismic events in mines (Finnie, 1999), as intelligence amplification tool (Poulton, 2002), locating buried objects (Brown and Poulton, 1996), borehole resistivity modeling (Zhang et al, 2002), lithology log estimation (McCormack, 1991;Rogers et al, 1992;Chen and Fang, 1993;, log interpretation (Pezeshk et al, 1996), permeability prediction from well logs (Rogers et al, 1992;Huang et al, 1996), reservoir parameter estimation (Aminzadeh et al, 2000;Lingireddy, 1998), reservoir characterization (An and Moon, 1993), prediction of transient water levels in subsurface (Coppola et al, 2003), run off prediction (Elshorbagy and Simonovic, 2000), characterization of aquifer properties (Rizzo and Dougherty, 1994), in modeling soil water retention curves (Schaap and Boulten, 1996), in simulating the rainfall-runoff (Abrahart and Kneale, 1997;Abrahart and See, 1988;Hsu et al, 1995;Smith and Eli, 1995)...…”

A procedure of parameter inversion for a nonlinear constitutive model of soils with shield tunneling

“…Thus, the efficiency and productivity of the excavation can be increased and the associated cost can be reduced. Commonly used parameter identification procedures include using optimization procedures [1,2], genetic algorithms [3,4], neural networks [4,5], evolution algorithms [6], particle swarm optimizations [7], ant colony system algorithms, calibration methods [8], hybrid optimization algorithms [9], and Levenberg-Marquardt algorithms [10,11]. Shield tunneling has become a well-established tunnel construction method for various ground conditions.…”