In this study, an artificial neural network based model for prediction of solar energy potential in Kerman province in Iran has been developed. Meteorological data of 12 cities for period of 17 years (1997–2013) and solar radiation for five cities around and inside Kerman province from the Iranian Meteorological Office data center were used for the training and testing the network. Meteorologic...

Quantifying groundwater flow at seepage faces is crucial because seepage faces influence the hydroecology and water budgets of watersheds, lakes, rivers and oceans, and because measuring groundwater fluxes directly in aquifers is extremely difficult. Seepage faces provide a direct and measurable groundwater flux but there is no existing method to quantitatively image groundwater processes at th...

in this paper, time-domain dynamic analysis of dam - infinite reservoir is studied. a numerical method, discrete singular convolution (dsc), which seems to be efficient and simple, has been used to model the mixed boundary conditions. after a brief introduction, dsc is applied to model the equation of motion of fluid-structure with constant cross section subjected to el-centro (1940) earthquake...

This paper focuses on the problem of finite-time boundedness and finite-time passivity of discrete-time T-S fuzzy neural networks with time-varying delays. A suitable Lyapunov--Krasovskii functional(LKF) is established to derive sufficient condition for finite-time passivity of discrete-time T-S fuzzy neural networks. The dynamical system is transformed into a T-S fuzzy model with uncertain par...