A wide variety of radio propagation models for different wireless services that specifically address varying propagation environments and operating frequency bands are generally known (Pahlavan et al. 1995; Jakes 1974). A large number of propagation prediction models have been developed for various terrain irregularities, tunnels, urban streets and buildings, earth curvature, etc. (E. Vehicular...

Implementations of wireless network wave propagation models are necessary to determine propagation characteristic through a medium. Propagation study provides an estimation of signal characteristics. This paper evaluates about propagation models, their path loss behavior, propagation mechanisms, and propagation prediction techniques. A propagation model is a set of mathematical expressions, dia...

Petri net faulty models are useful for reliability analysis and fault diagnosis of discrete event systems. Such models are difficult to work out as long as they must be computed according to alarm propagation. This paper deals with Petri net models synthesis and identification based on neural network approaches, with regard to event propagation and to state propagation dataset. A learning neura...

it is necessary to use empirical models for estimating of instantaneous peak discharge because of deficit of gauging stations in the country. hence, at present study, two models including artificial neural networks and nonlinear multivariate regression were used to predict peak discharge in taleghan watershed. maximum daily mean discharge and corresponding daily rainfall, one day antecedent and...

The main task in designing of any wireless communication system is to predict the coverage of the planned system using some mathematical path loss models before the original design of the system. Propagation path loss models are very much useful mathematical tools to calculate signal attenuation and it can be used as a controlling factor for the system performance and coverage. The propagation ...