evaporation is one of the most important components of hydrologic cycle.accurate estimation of this parameter is used for studies such as water balance,irrigation system design, and water resource management. in order to estimate theevaporation, direct measurement methods or physical and empirical models can beused. using direct methods require installing meteorological stations andinstruments ...

This chapter considers the relationship between neural field and mass models and their application to modelling empirical data. Specifically, we consider neural masses as a special case of neural fields, when conduction times tend to zero and focus on two exemplar models of cortical microcircuitry; namely, the Jansen-Rit and the Canonical Microcircuit Model. Both models incorporate parameters p...

Motivated by the advantages achieved by implicit analogue net for solving online linear equations, a novel implicit neural model is designed based on conventional explicit gradient neural networks in this letter by introducing a positive-definite mass matrix. In addition to taking the advantages of the implicit neural dynamics, the proposed implicit gradient neural networks can still achieve gl...

in recent years, the existing competitions between investment companies have been increased largely by entering private investors in capital market. large and powerful companies try to achieve the goals predicted to increase the competition capacity. to analyze the efficiency of investment companies, parametric and non-parametric methods are used. in this research, based on the dissociation pow...

This paper describes a neural model of speech production and perception-production interactions. This model has been developed to account for a wide variety of experimental data, ranging from kinematic analyses of articulator movements to functional imaging studies of the human brain. We have also tested predictions based on the model with these and other experimental techniques. Hypothesized n...

abstract tax is one of the main sources of financing government budget. therefore, having a clear picture about the attainable amount of taxes are not only necessary for optimal allocation of scarce resources for tax collection, but also helps the government to develop precise tax collection programs .in this article, the structural features of the tax revenues series have first been examined i...

this paper presents a prediction model based on a new neuro-fuzzy algorithm for estimating time in construction projects. the output of the proposed prediction model, which is employed based on a locally linear neuro-fuzzy (llnf) model, is useful for assessing a project status at different time horizons. being trained by a locally linear model tree (lolimot) learning algorithm, the model is int...

an adaptive input-output linearization method for general nonlinear systems is developed without using states of the system. another key feature of this structure is the fact that, it does not need model of the system. in this scheme, neurolinearizer has few weights, so it is practical in adaptive situations.  online training of neurolinearizer is compared to model predictive recurrent training...

in this study, a hybrid intelligent model has been designed to predict groundwater inflow to a mine pit during its advance. novel hybrid method coupling artificial neural network (ann) with genetic algorithm (ga) called ann-ga, was utilised. ratios of pit depth to aquifer thickness, pit bottom radius to its top radius, inverse of pit advance time and the hydraulic head (hh) in the observation w...