in the present study, an application of multilevel modeling approach to the input- output analysis are presented first, the regional input-output table of all provinces in iran was extracted based on the adjusted flegg location quotient method (aflq). second differentiation in the leontief technical coefficients and the backward and forward linkages among various activities and sectors of all p...

Electrical impedance tomography (EIT) is a non-invasive imaging technique where a conductivity distribution in a domain is reconstructed from boundary voltage measurements. The voltage data are generated by injecting currents into the domain. This is an ill-conditioned non-linear inverse problem. Small measurement or forward modeling errors can lead to unbounded fluctuations in the reconstructi...

We focus on the Forward Problem of electroencephalography, discuss a mathematical model and state properties of its weak solutions. A static and a timedependent model for the source are considered. Numerical solutions, obtained by a Boundary Element Method technique, are compared with the analytical ones and with EEG recordings. Keywords– EEG, Forward Problem, Epilepsy, Modeling

Accurate models of Overcurrent (OC) with inverse time relay characteristics play an important role for coordination of power system protection schemes. This paper proposes a new method for modeling OC relays curves. The model is based on fuzzy logic and artificial neural networks. The feed forward multilayer perceptron neural network is used to calculate operating times of OC relays for various...

detection of subsurface structures by means of gravity method can be used to determine mass distribution and density contrast of rock units. this distribution could be detected by different geophysical methods, especially gravity method. however, gravity techniques have some drawbacks and can't be always successful in distinguishing subsurface structures. performance of the gravity technique co...

In this paper, a novel MIMO Neural NARX model is used for simultaneously modeling and identifying both joints of the 2-axes PAM robot arm’s inverse and forward dynamic model. The highly nonlinear cross effect of both links of the 2-axes PAM robot arm are thoroughly modeled through an Inverse and Forward Neural MIMO NARX Model-based identification process using experimental input-output training...

An artificial neural network has been used to determine the volume flux and rejections of Ca2+ , Na+ and Cl¯, as a function of transmembrane pressure and concentrations of Ca2+, polyethyleneimine, and polyacrylic acid in water softening by nanofiltration process in presence of polyelectrolytes. The feed-forward multi-layer perceptron artificial neural network including an eight-neuron hidde...

Super-resolution (SR) is the area of research and development which produces one or a set of high-resolution images from one or a set of low-resolution frames. In this paper, first, a short review of a variety of SR problems is presented. Then, starting by a single input single output case, we present different forward modeling of 1D or 2D SR problems. We focus then on the multi input single ou...

We apply the residual terrain modeling (RTM) technique for gravity forward-modeling to successfully improve high-resolution global gravity fields at short spatial scales in coastal zones. The RTM scheme is combined with the concept of rock-equivalent topography, allowing to use a single uniform constant mass-density in the RTM forward-modeling, both at land and sea. SRTM30_PLUS bathymetry is me...