in this paper, based on a new keynesian structure, we have analyzed monetary policy response to exchange rate volatilities in iran. for this purpose, first, exchange rate derived from equilibrium condition in exchange market and then two different models have been estimated. assumption on the first model is that central bank responses to exchange rate volatilities and the assumption on the seco...

The rate of penetration (ROP) is one of the vital parameters which directly affects the drilling time and costs. There are various parameters that influence the drilling rate; they include weight on bit, rotational speed, mud weight, bit type, formation type, and bit hydraulic. Several approaches, including mathematical models and artificial intelligence have been proposed to predict the rate o...

    The article attempts to have neural network and genetic algorithm techniques present a model for classification on dataset. The goal is design model can the subject acted a firewall in network and this model with compound optimized algorithms create reliability and accuracy and reduce error rate couse of this is article use feedback neural network and compared to previous methods increase a...

this paper investigates the effect of exchange rate uncertainty on the iran’s import trade. the exchange rate ‎uncertainty series were generated utilizing the tarch model. this model analyzes the asymmetric effects. the analysis of uncertainty and asymmetry ‎of the exchange rate shows significant tarch ‎effect on iran’s exchange rates‎. the findings of the study indicate negative shocks (bad ne...

T he main purpose of this article is to analyze exchange rate behavior based on monetary fundamentals in the context of Iranian economy over the period 1990:2 to 2014:3. To do so, two monetary exchange rate models is investigated, the first by regarding interest rate differential as a monetary variable, and the second one regardless of interest rate differential as a monetary variabl...

    The article attempts to have neural network and genetic algorithm techniques present a model for classification on dataset. The goal is design model can the subject acted a firewall in network and this model with compound optimized algorithms create reliability and accuracy and reduce error rate couse of this is article use feedback neural network and compared to previous methods increase a...

In this paper, we introduce a new Bathtub shaped failure rate model named as x-Exponantial Model and present a comparative study with Generalized Lindley, Generalized Gamma and Exponentiated Weibull distributions.

Previous research has shown a strong correlation of protein folding rates to the native state geometry, yet a complete explanation for this dependence is still lacking. Here we study the rate-geometry relationship with a simple statistical physics model, and focus on two classes of model geometries, representing ideal parallel and antiparallel structures. We find that the logarithm of the rate ...

We consider Bloch equations which govern the evolution of the density matrix of an atom (or: a quantum system) with a discrete set of energy levels. The system is forced by a time dependent electric potential which varies on a fast scale and we address the long time evolution of the system. We show that the diagonal part of the density matrix is asymptotically solution to a linear Boltzmann equ...

Rissanen’s Minimum Description Length (MDL) principle for model selection proposes that, among a predetermined collection of models, we choose the one which assigns the shortest description to the data at hand. In this context, a “description” is a lossless representation of the data that also takes into account the cost of describing the chosen model itself. We examine how the MDL principle mi...