This study focuses on evaluating the suitability of three interpolation methods in terms of their accuracy at climate data for some provinces of south of Iraq. Two data sets of maximum and minimum temperature in February 2008 from nine meteorological stations located in the south of Iraq using three interpolation methods. ArcGIS is used to produce the spatially distributed temperature data by using IDW, ordinary kriging, and spline. Four statistical methods are applied to analyze the results obtained from three interpolation methods. These methods are RMSE, RMSE as a percentage of the mean, Model efficiency (E) and Bias, which showed that the ordinary krigingis the best for this data from other methods by the results that have b

Multiple linear regressions are concerned with studying and analyzing the relationship between the dependent variable and a set of explanatory variables. From this relationship the values of variables are predicted. In this paper the multiple linear regression model and three covariates were studied in the presence of the problem of auto-correlation of errors when the random error distributed the distribution of exponential. Three methods were compared (general least squares, M robust, and Laplace robust method). We have employed the simulation studies and calculated the statistical standard mean squares error with sample sizes (15, 30, 60, 100). Further we applied the best method on the real experiment data representing the varieties of

rop simulation models play a pivotal role in evaluating irrigation management strategies to improve water use in agriculture. The aim of this study is to verify the validity of the Aquacrop model of maize under the surface and sprinkler irrigation systems, and a cultivation system, borders and furrows, and for two varieties of Maze (Fajr and Drakma) At two different sites in Iraq, Babylon and Al-Qadisiyah governorates. An experiment was conducted to evaluate the performance of the Aquacrop model in simulating canopy cover (CC), biomass (B), dry yield, harvest index (HI), and water productivity (WP). The results of RMSE, R2, MAE, d, NSE, CC, Pe indicated good results and high compatibility between measured and simulated values. The highest a

Porosity is important because it reflects the presence of oil reserves. Hence, the number of underground reserves and a direct influence on the essential petrophysical parameters, such as permeability and saturation, are related to connected pores. Also, the selection of perforation interval and recommended drilling additional infill wells. For the estimation two distinct methods are used to obtain the results: the first method is based on conventional equations that utilize porosity logs. In contrast, the second approach relies on statistical methods based on making matrices dependent on rock and fluid composition and solving the equations (matrices) instantaneously. In which records have entered as equations, and the matrix is sol

Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall

In recent years, it has been evident that searching for alternative methods with low-price and eco-friendly features that produce high-quality adsorbents is in high demand. In the present work, Rice husk from Iraqi rice named (Amber) had been used as the primary source to produce rice husk ash (RHA) for the removal of the antibiotic metronidazole (Flagyl) from water. After optimum drying of rice husk, rice husk ash (RHA) was obtained at 600 °C using an electric oven. RHA has been investigated for properties using X-ray diffraction (XRD), porosity, and surface area (SA). The experimental work adsorption data were optimized to evaluate Langmuir and Freundlich constants. The thermodynamic parameters likely a change in Gipp's energy (ΔG),

Abstract This research investigates how activated carbon (AC) was synthesized from potato peel waste (PPW). Different ACs were synthesized under the atmosphere's conditions during carbonation via two activation methods: first, chemical activation, and second, carbon dioxide-physical activation. The influence of the drying period on the preparation of the precursor and the methods of activation were investigated. The specific surface area and pore volume of the activated carbon were estimated using the Brunauer–Emmett–Teller method. The AC produced using physical activation had a surface area as high as 1210 m2/g with a pore volume of 0.37 cm3/g, whereas the chemical activation had a surface area of 1210 m2/g with a pore volume of 0.34 c