spatial-temporal modeling of air pollutants, ground-level ozone concentrations in particular, has attracted recent attention because by using spatial-temporal modeling, can analyze, interpolate or predict ozone levels at any location. in this paper we consider daily averages of troposphere ozone over tehran city. for eliminating the trend of data, a dynamic linear model is used, then some featu...

Spatial-temporal modeling of air pollutants, ground-level ozone concentrations in particular, has attracted recent attention because by using spatial-temporal modeling, can analyze, interpolate or predict ozone levels at any location. In this paper we consider daily averages of troposphere ozone over Tehran city. For eliminating the trend of data, a dynamic linear model is used, then some featu...

although, single-sided linear induction motor (slim) utilization has increased in railway applications due to their numerous advantages in comparison to rotational induction motors (rim), there are some sophistication in their mathematical models and electrical drive. this paper focuses on the problems of slim modeling, with assuming end-effect on the basis of field oriented control (foc) as a ...

this study concerns the scope to improve water flooding in heterogeneous reservoirs. we used an existing, in-house developed, optimization program consisting of a reservoir simulator in combination with an adjoint-based optimal control algorithm. in particular we aimed to examine the scope for optimization in a two-dimensional horizontal reservoir containing a single high permeable streak, as a...

monitoring and forecasting of air quality parameters in urban areas is considered as one of the challenges of the human environment. it depends on several factors such as topography, climate, population and transport network which the interaction of these spatial factors has been as a dynamic phenomenon, non-linear and ambiguous. in this study, two models suggested to predict and modeling conce...

an adaptive version of growing and pruning rbf neural network has been used to predict the system output and implement linear model-based predictive controller (lmpc) and non-linear model-based predictive controller (nmpc) strategies. a radial-basis neural network with growing and pruning capabilities is introduced to carry out on-line model identification.an unscented kalman filter (ukf) algor...