Numerical differentiation of fractional order derivatives based on inverse source problems of hyperbolic equations by Zewen Wang, Shufang Qiu, Xiuxing Rui, Wen Zhang

“…It can be conclude that the proposed methods are very effective for small noise levels, and they are simpler and easier to be implemented than the previous PDEs-based numerical differentiation method based on direct and inverse problems of parabolic equations. …”
Get full text

Magnetoacoustic Heating in Nonisentropic Plasma Caused by Different Kinds of Heating-Cooling Function by Anna Perelomova

“…The conclusions concern nonlinear effects of fast and slow magnetoacoustic perturbations and may be useful in direct and inverse problems.…”
Get full text

A Comparative Study of Regularization Method in Structure Load Identification by Bingrong Miao, Feng Zhou, Chuanying Jiang, Xiangyu Chen, Shuwang Yang

“…The proposed two kinds of load identification procedure based on vibration response can be applied to the safety performance evaluation of the railway track structure in future inverse problems research.…”
Get full text

Physics-informed deep learning quantifies propagated uncertainty in seismic structure and hypocenter determination by Ryoichiro Agata, Kazuya Shiraishi, Gou Fujie

“…Our results highlight the potential of PIDL for various geophysical inverse problems, such as investigating earthquake source parameters, which inherently suffer from uncertainty propagation.…”
Get full text

Load Identification Method Based on Interval Analysis and Tikhonov Regularization and Its Application by Chunsheng Liu, Chunping Ren, Nengjian Wang

“…By using the interval analysis method of the first-order Taylor expansion, the dynamic force identification is transformed into two kinds of deterministic inverse problems at the midpoint of the uncertain parameter and its gradient identification. …”
Get full text

Seismic Waveform Inversion Using the Finite-Difference Contrast Source Inversion Method by Bo Han, Qinglong He, Yong Chen, Yixin Dou

“…Another attractive feature of the inversion method is that it is of strong capability in dealing with nonlinear inverse problems in an inhomogeneous background medium, because a finite-difference operator is used to represent the differential operator governing the two-dimensional elastic wave propagation. …”
Get full text

Proximal Neural Networks based reconstruction for few-view CT applications by Hoang Trieu Vy Le, Caroline Bossuyt, Julie Escoda, Marius Costin, Jan De Beenhouwer, Jan Sijbers

“…Recent advancements in Plug-and-Play (PnP) algorithms have shown promise for solving imaging inverse problems by utilizing the capabilities of Gaussian denoising algorithms to handle complex optimization tasks. …”
Get full text

Two-Stage GPR Image Inversion Method Based on Multi-Scale Dilated Convolution and Hybrid Attention Gate by Mingze Wu, Qinghua Liu, Shan Ouyang

“…In practical applications, the complexity and nonuniformity of underground structures bring noise and clutter interference, making GPR inversion problems more challenging. To address these issues, this study proposes a two-stage GPR image inversion network called MHInvNet based on multi-scale dilated convolution (MSDC) and hybrid attention gate (HAG). …”
Get full text

Quantitative assessment of PINN inference on experimental data for gravity currents flows by Mickaël Delcey, Yoann Cheny, Jean Schneider, Simon Becker, Sébastien Kiesgen De Richter

“…PINNs are able to solve ill-posed inverse problems training on sparse and noisy data, and therefore can be applied to real engineering applications. …”
Get full text

Application of physics-informed neural networks (PINNs) solution to coupled thermal and hydraulic processes in silty sands by Yuan Feng, Jongwan Eun, Seunghee Kim, Yong-Rak Kim

“…Recently, physics-informed neural networks (PINNs), which incorporate partial differential equations (PDEs) to solve forward and inverse problems, have attracted increasing attention in machine learning research. …”
Get full text

A Discrete Dipole Approximation Solver Based on the COCG-FFT Algorithm and Its Application to Microwave Breast Imaging by Samar Hosseinzadegan, Andreas Fhager, Mikael Persson, Paul Meaney

“…We introduce the discrete dipole approximation (DDA) for efficiently calculating the two-dimensional electric field distribution for our microwave tomographic breast imaging system. For iterative inverse problems such as microwave tomography, the forward field computation is the time limiting step. …”
Get full text

From lab to landscape-scale experiments for the morphodynamics of sand dunes by Claudin, Philippe, Courrech du Pont, Sylvain, Narteau, Clément

“…This understanding can serve as a foundation for further investigations, including the interpretation of dune landscapes and the resolution of inverse problems.…”
Get full text

On Damage Identification in Planar Frames of Arbitrary Size by I. Fiore, A. Greco, A. Pluchino

“…The natural frequencies obtained by means of the proposed approach are used for the solution of two different inverse problems, which concern the identification of, respectively, the mechanical characteristics of the constitutive material and the location and intensity of the damage. …”
Get full text

Stratifications and foliations in phase portraits of gene network models by V. P. Golubyatnikov, A. A. Akinshin, N. B. Ayupova, L. S. Minushkina

“…In the preparation of numerical experiments with such mathematical models, it is useful to start with studies of qualitative behavior of ensembles of trajectories of the corresponding dynamical systems, in particular, to estimate the highest likelihood domain of the initial data, to solve inverse problems of parameter identification, to list the equilibrium points and their characteristics, to localize cycles in the phase portraits, to construct stratification of the phase portraits to subdomains with different qualities of trajectory behavior, etc. …”
Get full text

Advances in the pilot point inverse method: Où En Sommes-Nous maintenant? by White, Jeremy, Lavenue, Marsh

“…Herein, we provide an update to de Marsily’s paper entitled “Four Decades of Inverse Problems in Hydrogeology” [De Marsily et al., 2000], but with a particular focus on the incredible adoption and advancement of de Marsily’s PPM and related inverse techniques over the last twenty years in the field of predictive groundwater modeling.Much has been written about the vast array of inverse techniques developed by researchers and practitioners since the 1960s. de Marsily’s PPM, like many methods developed in the late 70s and early 80s, structured its approach to parameterization to overcome many of the challenges of applying inverse methods to real world problems, namely, limited head and transmissivity data relative to the number of unknowns to be estimated, measurement errors, inferred covariance structures of the state variables, and limited computational resources. …”
Get full text