A. Rezaei, M. Mahdavi, K. Luxe, S. Feiznia, M. H. Mahdian,
Volume 11, Issue 1 (spring 2007)
Abstract
The model in this research was created based on the Artificial Neural Network (ANN) and calibrated in the Sefid-rood dam basin (excluding Khazar zone). This research was done by gathering and selecting peak flows of hydrographs from 12 sub basins, the concentration time of which was equal to or less than 24 hours and was caused only by rainfall. From all the selected sub basins, totally 661 hydrographs were prepared and their peak flows data wes used to make prediction model. The input variables of the model consisted of the depth of daily flooding rainfalls, and so the five days before rainfall of every peak flow, the area of sub basins, the main stream length, the slope of 10-85 percent of main stream, the median height of sub basins, the area of geological formations and rock units, classified at three hydrological groups of I, II, III, the base flow, and output variable was only peak flow. By using Feed Forward Artificial Neural Network with training method of back propagation error the function approximation of inputs to output was created by passing the three processes of training (learning), testing and validation. So based on that data and variables, the Multivariable Linear Regression model was created. The comparison of observed peak flows, based on validation data package, showed that the statistical parameters of (R2) coefficient and Fisher’s test parameter coefficient (F) for ANN model and MLR respectively were 0.84, 33.66 and 0.33, 3.60, indicating the superiority of ANN to traditional methods.
Z. Nazari, N. Khorasani, S. Feiznia, M. Karami,
Volume 22, Issue 1 (Spring 2018)
Abstract
The purpose of this research was source identification of aerosols in atmosphere using geochemical properties in the city of Kermanshah. The concentrations of twenty elements consisting of K, Na, Ca, P, Cu, Ni, Pb, Cd, Se, Zn, Fe, Mg, B, Cr, Co, As, Mo, V were analyzed by ICP for 55 soil samples (in the height range of 600-1600m) and 41 aerosols samples. Source identification of aerosels using geochemical tracers was performed in two steps. In the first step, appropriate combination of tracer elements with high ability in the resolation of aerosol sources was chosen using the means comparison test and discriminate analysis. In the second step, the multivariate mixing model was used to determine the contribution of aerosol sources (geological and geomorphology types) to the production of aerosols in the study area. The results obtained from determination of the contributions of sources of aerosols (geological and geomorphological types) showed the UF formation (consisting of red marl and sandstone), with the height of 0-1400 mand the slope of 0-5%, could be regarded as the main contributor to the production of aerosols located in the city of Qasreshirin.
