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Showing 2 results for Khalilimoghadam
Parametric Estimation of the Van Genuchten and Fredlund and Xing’s Moisture Retention Curve Models Using Soft Computing Techniques in Some Khozestan Soils
F. Moradi, B. Khalilimoghadam, S. Jafari, S. Ghorbani Dashtaki,
Volume 18, Issue 69 (fall 2014)
Abstract

Soft computing techniques have been extensively studied and applied in the last three decades for scientific research and engineering computing. The purpose of this study was to investigate the abilities of multilayer perceptron neural network (MLP) and neuro-fuzzy (NF) techniques to estimate the soil-water retention curve (SWRC) from Khozestan sugarcane Agro-Industries data. Sensitivity analysis was used for determining the model inputs and appropriate data subset. Also, in this paper, the van Genuchten and Fredlund and xing models were used to predict SWRC. Measured soil variables included particle size distribution, organic matter, bulk density, calcium carbonate, sodium adsorption ratio, electrical conductivity, acidity, mean weight diameter, plastic and liquid limit, resistance of soil penetration, water saturation percentage and water content for matric potentials -33, -100, -500 and -1500 kPa. The results of this study in terms of various statistical indices indicated that both MLP and NF provide good predictions but the neural network provides better predictions than neuro-fuzzy model. For example, using MLP and NF models values of NMSE at prediction θs, θr, α, n and m in Fredlund and Xing equation corresponded to (0.059, 0.065), (0.154, 0.162), (0.109, 0.117), (0.129, 0.135) and (0.129, 0.145), respectively. Furthermore, α and n parameters at the first depth, and θr and α parameters at the second depth in Fredlund and Xing equation were estimated with higher accuracy compared with equivalent parameters in van Genuchten equation


Investigation of the Amount and Possible Source of Polycyclic Aromatic Hydrocarbons (PAHs) in the Dust Deposited on the Leaves of Trees in Ahvaz
B. Khalilimoghadam, A. Siadat, A. Yusefi,
Volume 25, Issue 1 (Spring 2021)
Abstract
Dust deposited on the leaves of trees can be effectively used as the monitors of polycyclic aromatic hydrocarbons (PAHs). The dust deposited on the leaves can be used as an appropriate index for evaluating PAHs in the atmosphere. This research was conducted to determine the origin and health risk assessment of PAHs accumulated on the leaves of trees in the city of Ahvaz. For this purpose, samples were taken at leaves on 10 points with different land uses including industrial, recreational, high-traffic and residential ones. After preparation, to determine the type and concentration of PAHs, the compounds were analyzed by GC-MS. The results showed that 15 types of PAHs had been identified from 16 important compounds identified by EPA in the dust samples. The concentration of compounds was the range of 3.3-110 microgram per kilogram. The maximum and minimum of PAHs carcinogenic in particles trapped on leaves were in the Kut-Abdolah with 530 ppb and Shahrvand Park Station with 5.13 ppb, respectively. Also, the average relative of LMW/HMW in the aromatics contained in the deposition of particles on trees was 0.5; further the analysis of the main components of aromatic hydrocarbons (PAHs) showed that there was  no specific source for these compounds in Ahvaz, and these compounds could be from fossil fuels, urban traffic, natural gas,   generally showing a pyrogenic origin.

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