In this article, we survey machine repair problems (MRP) with an emphasis on historical developments of queuing models of practical importance. The survey proceeds historically, starting with developments in 1985, when the first published review on machine interference models appeared. We attempt to elaborate some basic MRP models of the real life congestion situations. The brief survey of some...

Statistical methods, and especially machine learning, have been increasingly used in nanofluid modeling. This paper presents some of the interesting and applicable methods for thermal conductivity prediction and compares them with each other according to results and errors that are defined. The thermal conductivity of nanofluids increases with the volume fraction and temperature. Machine learni...

Statistical methods, and especially machine learning, have been increasingly used in nanofluid modeling. This paper presents some of the interesting and applicable methods for thermal conductivity prediction and compares them with each other according to results and errors that are defined. The thermal conductivity of nanofluids increases with the volume fraction and temperature. Machine learni...

klinkenberg permeability is an important parameter in tight gas reservoirs. there are conventional methods for determining it, but these methods depend on core permeability. cores are few in number, but well logs are usually accessible for all wells and provide continuous information. in this regard, regression methods have been used to achieve reliable relations between log readings and klinke...

in this work some quantitative structure activity relationship models were developed for prediction of three bioenvironmental parameters of 28 volatile organic compounds, which are used in assessing the behavior of pollutants in soil. these parameters are; half-life, non dimensional effective degradation rate constant and effective péclet number in two type of soil. the most effective descripto...

in this work, several machine learning techniques are presented for nanofiltration modeling. according to the results, specific errors are defined. the rejection due to nanofiltration increases with pressure but decreases with increasing the concentration of chloride ion. methods of machine learning represent the rejection of nanofiltration as a function of concentration, ph, pressure and also ...

Klinkenberg permeability is an important parameter in tight gas reservoirs. There are conventional methods for determining it, but these methods depend on core permeability. Cores are few in number, but well logs are usually accessible for all wells and provide continuous information. In this regard, regression methods have been used to achieve reliable relations between log readings and Klinke...

the support vector machine (svm) is a relatively new machine learning method which is increasingly being applied to engineering problems and have yielded encouraging results. because of complex behavior of elastoplastic of web panels of plate girders under patch loading, almost none of the proposed methods provides consistent and accurate predictions of patch load capacity. consequently, altern...

In this Paper, complete models of three and six phase self commutated synchronous machine drives are presented, considering the effects of both time and space harmonics. First, the equations for calculation of machine inductances are developed. Next, "thyristor-inverter-electric machine" set is modeled in order to derive all the equations for conduction and commutation states. Finally, the resu...