data envelopment analysis (dea) is a wide range of mathematical models that used for measuring the relative efficiency of a set of harmonic units whit similar inputs and outputs. this model calculates some different weight for input and output variables in each decision making model. this variation in similar weights caused some critiques to this method. from 1991 some linear and nonlinear mode...

Theoretical and empirical research suggests that job experience, organizational tenure, and age have non-linear relationships with performance. Considered simultaneously, there should exist an inverted U-shaped relationship between time and performance. This paper includes three studies — a meta-analysis, a crosssectional sample, and a longitudinal sample—to test these hypotheses. Together, the...

A non-linear gravitational model with a multidimensional geometry and quadratic scalar curvature is considered. For certain parameter ranges, the extra dimensions are stabilized if the internal spaces have negative constant curvature. As a consequence, the 4–dimensional effective cosmological constant as well as the bulk cosmological constant become negative. The homogeneous and isotropic exter...

background and objectives: efficient cost management in hospitals’ pharmaceutical inventories have thepotential to remarkably contribute to optimization of overall hospital expenditures. to this end, reliable forecasting models for accurate prediction of future pharmaceutical demands are instrumental. while the linear methods are frequently used for forecasting purposes chiefly due to their sim...

This article reviews techniques to identify the frequency domain properties of linear and nonlinear systems from measured physical input/output data. Practical spectral analysis procedures are discussed that are valid with random data to predict the frequency response functions in single-input/single-output (SI/SO) linear models and in multipleinput/single-output (MI/SO) linear models. Special ...

The quantitative structure-retention relationship (QSRR) of nanoparticles in roadside atmosphere against the comprehensive two-dimensional gas chromatography which was coupled to high-resolution time-of-flight mass spectrometry was studied. The genetic algorithm (GA) was employed to select the variables that resulted in the best-fitted models. After the variables were selected, the linear multi...

‎In this paper‎, ‎the nonlinear regression models when the model errors follow a slash‎ ‎skew-elliptical distribution‎, ‎are considered‎. ‎In the special case‎ ‎of nonlinear regression models under slash skew-t distribution‎, ‎we‎ ‎present some distributional properties‎, ‎and to estimate their‎ ‎parameters‎, ‎w...

neural mass models are computational nonlinear models that simulate the activity of a population of neurons as an average neuron, in such a way that different inhibitory post synaptic potential (ipsp) and excitatory post synaptic potential (epsp) signals could be reproduced. these models have been developed either to simulate the recognized neural mechanisms or to predict some physiological fac...

Accurate models of Overcurrent (OC) with inverse time relay characteristics play an important role for coordination of power system protection schemes. This paper proposes a new method for modeling OC relays curves. The model is based on fuzzy logic and artificial neural networks. The feed forward multilayer perceptron neural network is used to calculate operating times of OC relays for various...

friction is a nonlinear phenomenon which has destructive effects on performance of control systems. to obviate these effects, friction compensation is an effectual solution. in this paper, an adaptive technique is proposed in order to eliminate limit cycles as one of the undesired behaviors due to presence of friction in control systems which happen frequently. the proposed approach works for n...