the price of oil plays an important role in the global economy and is an important factor influencing the government and commercial sectors. because of increasing importance of oil in financial markets, oil price predictions have always been an important subject for the researchers in economics, and other economic agents. this paper tries to study the behavior of crude oil prices based on smoot...

Normal 0 false false false EN-US X-NONE AR-SA MicrosoftInternetExplorer4 Measurement of solar radiance demands expensive devices to be used. Alternatively, estimator models are used instead. In this paper, a new method based on the empirical equations is introduced to estimate the monthly average daily global solar radiation on a horizontal surface. The proposed method uses Intelligent Water ...

Monthly and yearly gross primary productivity (GPP) estimates derived from an empirical and two process based models (3PG and BIOMASS) were compared. Spatial and temporal variation in foliar gas photosynthesis was examined and used to develop GPP prediction models for fertilized nine-year-old loblolly pine (Pinus taeda) stands located in the North Carolina Sandhills. Foliar gas exchange in both...

Considering the fact that natural gas is a widely used energy source,  the prediction of its consumption can be useful (Derek LAM, 2013). As Iran has one of the largest gas reserves in the world, its consumption in the country can affect the worldwide price of gas, Therefore, the current research is useful both from economic and environmental point of view. ...

Considering the advantage of Empirical Mode Decomposition (EMD) for extracting geophysical signals and filtering out noise, this paper will first apply EMD approach to post-process Gravity Recovery Climate Experiment (GRACE) monthly gravity field models. A 14-year time-series Release 06 (RL06) models from Center Space Research (CSR) truncated degree order 60 period April 2002 August 2016 are an...

Abstract Accurate measurements of available water resources play a key role in achieving sustainable environment society. Precise river flow estimation is an essential task for optimal use hydropower generation, flood forecasting, and best utilization engineering. The current paper presents the development verification prediction abilities new hybrid extreme learning machine (ELM)-based models ...

the present research was planned to evaluate the skill of linear stochastic models known as arima and multiplicative seasonal autoregressive integrated moving average (sarima) model in the quantitative forecasting of the standard runoff index (sri) in karkheh basin. to this end, sri was computed in monthly and seasonal time scales in 10 hydrometric stations in 1974-75 to 2012-13 period of time ...