In this paper statistical and time series models are used for determining the random drift of a dynamically Tuned Gyroscope (DTG). This drift is compensated with optimal predictive transfer function. Also nonlinear neural-network and fuzzy-neural models are investigated for prediction and compensation of the random drift. Finally the different models are compared together and their advantages a...

abstract prediction of input flow into water resources is regarded as one of the most important issues in optimum planning and management in producing electro-water energy and optimum allocation of water into different consumption sources. different parameters affect on input discharge into dams. climate variables including temperature and rainfall have the most effect on input runoff rate to w...

introduction: accurate water demand modeling for the city is very important for forecasting and policies adoption related to water resources management. thus, for future requirements of water estimation, forecasting and modeling, it is important to utilize models with little errors. water has a special place among the basic human needs, because it not hampers human life. the importance of the i...

background: this study attempted to investigate traffic accident fatalities during 2004-2009 and the effect of fuel rationing on traffic accident fatalities .   materials and methods: this was a cross-sectional study on available data of all traffic accident fatalities in fars province, iran, during 2004-2009. to identify and fit the best model, various instruments, including the autocorrelatio...

multiple sclerosis (ms) is one of the autoimmune diseases with an unknown cause. the aim of this study was to explore the link between air quality and ms relapses in patients who suffer from ms.this time-series study was conducted on patients registered at the iranian multiple sclerosis society in 2011-2012. they were randomly selected from patients lived in tehran in the last five years, and h...

This paper draws attention to the limitations of the standard unit root/cointegration approach to economic and financial modelling, and to some of the alternatives based on the idea of fractional integration, long memory models, and the random field regression approach to nonlinearity. Following brief explanations of fractional integration and random field regression, and the methods of applyin...