Load modeling is widely used in power system studies. Two types of modeling, namely, static and dynamic, are employed. The current industrial practice is the static modeling. Static modelss are algebraic equations of active and reactive power changes in terms of voltage and frequency deviations. In this paper, a component based on static modeling is employed in which the aggregate model is deri...

this study investigates the oil extraction from pistacia khinjuk by the application of enzyme.artificial neural network (ann) and adaptive neuro fuzzy inference system (anfis) were applied formodeling and prediction of oil extraction yield. 16 data points were collected and the ann was trained with onehidden layer using various numbers of neurons. a two-layered ann provides the best results, us...

in this paper, a novel hybrid model based on neural network and game theory is proposed to support the analyzers in oil market. in this model, first the neural network is utilized to learn the oil prices associated with opec production level and usa imports level. then the learned neural network is applied by a game model. finally the nash equilibrium points of the game present the optimum deci...

modeling of stream flow–suspended sediment relationship is one of the most studied topics in hydrology due to itsessential application to water resources management. recently, artificial intelligence has gained much popularity owing toits application in calibrating the nonlinear relationships inherent in the stream flow–suspended sediment relationship. thisstudy made us of adaptive neuro-fuzzy ...

Embryogenesis, regeneration and cell differentiation in microbiological entities are influenced by mechanical forces. Therefore, development of mechanical properties of these materials is important. Neural network technique is a useful method which can be used to obtain cell deformation by the means of force-geometric deformation data or vice versa. Prior to insertion in the needle injection pr...

many efforts have been made to model the the hot deformation (dynamic recrystallization) flow curves of different materials. phenomenological constitutive models, physical-based constitutive models and artificial neural network (ann) models are the main methods used for this purpose. however, there is no report on the modeling of warm deformation (dynamic spheroidization) flow curves of any kin...

background : the study examined the implementation of artificial neural network (ann) for the prediction of ammonia nitrogen removal from landfill leachate by ultrasonic process. methods : a three-layer backpropagation neural network was optimized to predict ammonia nitrogen removal from landfill leachate by ultrasonic process. considering the smallest mean square error (mse), the configuration...