In this paper we used frequentist and Bayesian approaches for the linear regression model to predict future observations for unemployment rates in Iraq. Parameters are estimated using the ordinary least squares method and for the Bayesian approach using the Markov Chain Monte Carlo (MCMC) method. Calculations are done using the R program. The analysis showed that the linear regression model using the Bayesian approach is better and can be used as an alternative to the frequentist approach. Two criteria, the root mean square error (RMSE) and the median absolute deviation (MAD) were used to compare the performance of the estimates. The results obtained showed that the unemployment rates will continue to increase in the next two decades.
Generally, direct measurement of soil compression index (Cc) is expensive and time-consuming. To save time and effort, indirect methods to obtain Cc may be an inexpensive option. Usually, the indirect methods are based on a correlation between some easier measuring descriptive variables such as liquid limit, soil density, and natural water content. This study used the ANFIS and regression methods to obtain Cc indirectly. To achieve the aim of this investigation, 177 undisturbed samples were collected from the cohesive soil in Sulaymaniyah Governorate in Iraq. Results of this study indicated that ANFIS models over-performed the Regression method in estimating Cc with R2 of 0.66 and 0.48 for both ANFIS and Regre
... Show MoreUrban land price is the primary indicator of land development in urban areas. Land prices in holly cities have rapidly increased due to tourism and religious activities. Public agencies are usually facing challenges in managing land prices in religious areas. Therefore, they require developed models or tools to understand land prices within religious cities. Predicting land prices can efficiently retain future management and develop urban lands within religious cities. This study proposed a new methodology to predict urban land prices within holy cities. The methodology is based on two models, Linear Regression (LR) and Support Vector Regression (SVR), and nine variables (land price, land area,
... Show MoreThe research is summarized in the construction of a mathematical model using the most common methods in the science of Operations Research, which are the models of transportation and linear programming to find the best solution to the problem of the high cost of hajj in Iraq, and this is done by reaching the optimum number of pilgrims traveling through both land ports and the number Ideal for passengers traveling through airports by Iraqi Airways, instead of relying on the personal experience of the decision-maker in Hajj and Umrah Authority by identifying the best port for pilgrim's travel, which can tolerate right or wrong, has been based on scientific methods of Operations Research, the researcher built two mathematical models
... Show MorePolycystic ovary syndrome(PCOS) is a heterogeneous disorder of uncertain etiology , it is the most common endocrinopathy in women and most common cause of anovulatery infertility ,characterized by chronic anovulation and hyperandrogenemia .The present study was designed to investigate the effect of silymarin which is known to have antioxidant and insulin sensitivity effects on the levels of glucose, insulin ,testosterone ,leutinizing hormone(LH) and progesterone .Ovulation rate and Homeostasis Model Assessment of insulin Resistance (HOMA) ratio were determined .A 3-months of treatment were conducted in 60 PCOS patients in three well-matched groups .The first one (n=20),received silymarin(750mg/day) .The second group received
... Show MoreThe measurement data of the raw water quality of Tigris River were statistically analyzed to measure the salinity value in relation to the selected raw water quality parameters. The analyzed data were collected from five water treatment plants (WTPs) assembled alongside of the Tigris River in Baghdad: Al-Karkh, Al-Karama, Al-Qadisiya, Al-Dora, and Al-Wihda for the period from 2015 to 2021. The selected parameters are total dissolved solid (TDS), electrical conductivity (EC), pH and temperature. The main objective of this research is to predicate a mathematical model using SPSS software to calculate the value of salinity along the river, in addition, the effect of electrical conductivi