Physics-informed Neural Network (PINN) is a promising tool that has been applied in variety of physical phenomena described by partial differential equations (PDE). However, it observed PINNs are difficult to train certain “stiff” problems, which include various nonlinear hyperbolic PDEs display shocks their solutions. Recent studies added diffusion term the PDE, and an artificial viscosity (AV...

The issue of credit risk and deferred bank claims is one of the sensitive issues of banking industry, which can be considered as the main cause of bank failures. In recent years, the economic slowdown accompanied by inflation in Iran has led to an increase in deferred bank claims that could put the country's banking system in serious trouble. Accordingly, the current paper presents a prediction...

in common classical methods of cavity depth estimation through microgravity data, usually when a pre-geometrical model is considered for the cavity shape, the simple geometrical models of sphere, vertical cylinder and horizontal cylinder are commonly used. it is obviously an important fact that in real conditions the shapes of the cavities are not exactly sphere, horizontal cylinder or vertical...

Lithofacies identi®cation supplies qualitative information about rocks. Lithofacies represent rock textures and are important components of hydrocarbon reservoir description. Traditional techniques of lithofacies identi®cation from core data are costly and di€erent geologists may provide di€erent interpretations. In this paper, we present a lowcost intelligent system consisting of three adaptiv...

The development of engineering applications of neural networks makes it necessary to clarify the similarities and differences between the concepts and methods developed for neural networks and those used in more classical fields such as filtering and control. In previous papers [Nerrand et al. 1993], [Marcos et al. 1993], the relationships between non-linear adaptive filters and neural networks...

the work exposure conditions such as dust concentration, exposure time, use of respiratory protection devices and smoking status are effective to cause pulmonary function disorder. the objective of this study was prediction of pulmonary disorders in workers exposed to silica dust using artificial neural networks and logistic regression. a sample of 117 out of 150 workers employed in the stone c...

in this paper, a novel hybrid method based on learning algorithmof fuzzy neural network and newton-cotesmethods with positive coefficient for the solution of linear fredholm integro-differential equation of the second kindwith fuzzy initial value is presented. here neural network isconsidered as a part of large field called neural computing orsoft computing. we propose alearning algorithm from ...