the purpose of this paper is to studying nonlinear k-ε turbulence models and its advantages in internal combustion engines, since the standard k-ε model is incapable of representing the anisotropy of turbulence intensities and fails to express the reynolds stresses adequately in rotating flows. therefore, this model is not only incapable of expressing the anisotropy of turbulence in an engine c...

modeling and analysis of future prices has been hot topic for economic analysts in recent years. traditionally, the complex movements in the prices are usually taken as random or stochastic process. however, they may be produced by a deterministic nonlinear process. accuracy and efficiency of economic models in the short period forecasting is strategic and crucial for business world. nonlinear ...

capital asset pricing model (capm) has been among the common models to estimate expected returns rate. since the linearity assumption is considered in the standard version of the capital asset pricing model, estimating beta in nonlinear setting will be inconsistent and bias-oriented. therefore, this study tries to evaluate predictive power of nonlinear capital asset pricing model as well as sta...

The purpose of this paper is to studying nonlinear k-ε turbulence models and its advantages in internal combustion engines, since the standard k-ε model is incapable of representing the anisotropy of turbulence intensities and fails to express the Reynolds stresses adequately in rotating flows. Therefore, this model is not only incapable of expressing the anisotropy of turbulence in an engine c...

nonlinear analyses allow simulating, in a more realistic way, the behaviour of structuressubjected to several types of complex loading conditions such as earthquakes. however, it isrecognized that these analyses normally generate a considerable amount of results, a factorthat difficult its interpretation. over the last years, considerable progresses have been made instructural nonlinear behavio...

in this paper, by investigating the common weights concept and dea models with nonlinear virtual inputs/outputs, we introduce a model for evaluating the decision making units with nonlinear virtual inputs and outputs based on the common weights.

comparison of linear and nonlinear (bilinear) time series models in reference crop evapotranspiration prediction in urmia synoptic stationreference crop evapotranspiration (eto) prediction is one of the important elements in optimizing agricultural water consumption. in this regard, one of the prediction approaches is to use the stochastic time series methods. in this research, ar (p) and arma(...

Time series and their methods of analysis are important subjects in statistics. Most of time series have a linear behavior and can be modelled by linear ARIMA models. However, some of realized time series have a nonlinear behavior and for modelling them one needs nonlinear models. For this, many good parametric nonlinear models such as bilinear model, exponential autoregressive model, threshold...