Infrastructure, especially wastewater projects, plays an important role in the life of residential communities. Due to the increasing population growth, there is also a significant increase in residential and commercial facilities. This research aims to develop two models for predicting the cost and time of wastewater projects according to independent variables affecting them. These variables have been determined through a questionnaire distributed to 20 projects under construction in Al-Kut City/ Wasit Governorate/Iraq. The researcher used artificial neural network technology to develop the models. The results showed that the coefficient of correlation R between actual and predicted values were 99.4% and 99 %, MAPE was

The study aims to study the geographical distribution of electricpower plants in Iraq, except the governorates of Kurdistan Region (Dohuk, Erbil, Sulaymaniyah) due to lack of data.

In order to reach the goal of the research was based on some mathematical equations and statistical methods to determine how the geographical distribution of these stations (gas, hydropower, steam, diesel) within the provinces and the concentration of them as well as the possibility of the classification of power plants in Iraq to facilitate understanding of distribution in a scientific manner is characterized by objectively.

The most important results of the research are that there are a number of factors that led to the irregular distribution

The present research is descriptive and analytical by nature; it practically presents the method of implementing the standard pattern in an unconventional way using the bias-cut line. The study aims at investigating the variables of bias-cut and their suitability for fitting large-shaped Iraqi ladies. It also aims at exploring the artistic and innovative features of the bias-cut. Therefore, one needs to understand the rules and basics of clothing and the nature of the body to reach the maximum degree of control.Consequently, the study is to answer the following questions: What is the effectiveness of tailoring on the bias-cut in fitting a standard template of a large-shaped Iraqi ladies? Is it possible to obtain from the offered possibil

The rental activity receives "significant" interest from accounting organizations interested in issuing accounting standards worldwide, such as the Financial Accounting Standards Board (FASB), the International Accounting Standards Board (IASB). As leases represents an important source of finance for economic units as an alternative to financing assets through purchase or borrowing. Professional organizations have focused on addressing the situation of extra-budgetary funding through which the lessee hides many leases that are classified as financing without It shows in the budget, which gives an incorrect picture of the reality of the financial situation of economic unity, IASB has issued IFRS 16, which terminates off- Balance s

A two time step stochastic multi-variables multi-sites hydrological data forecasting model was developed and verified using a case study. The philosophy of this model is to use the cross-variables correlations, cross-sites correlations and the two steps time lag correlations simultaneously, for estimating the parameters of the model which then are modified using the mutation process of the genetic algorithm optimization model. The objective function that to be minimized is the Akiake test value. The case study is of four variables and three sites. The variables are the monthly air temperature, humidity, precipitation, and evaporation; the sites are Sulaimania, Chwarta, and Penjwin, which are located north Iraq. The model performance was

 Researchers have increased interest in recent years in determining the optimum sample size to obtain sufficient accuracy and estimation and to obtain high-precision parameters in order to evaluate a large number of tests in the field of diagnosis at the same time. In this research, two methods were used to determine the optimum sample size to estimate the parameters of high-dimensional data. These methods are the Bennett inequality method and the regression method. The nonlinear logistic regression model is estimated by the size of each sampling method in high-dimensional data using artificial intelligence, which is the method of artificial neural network (ANN) as it gives a high-precision estimate commensurate with the dat

In this study was undertaken frish fish such as Bigeye Ilisha megaloptera, Nematalos nasus, Suboor Hilsha ilisha and Carp Cyprinus carpio. they were purchased from local marketes in Basrah, Oil was extracted by a solvent extraction method on low temperature. And the level of oil obtiened about (6.08; 10.72; 13.52 and 5.61)% for Bigeye, Jaffout, Suboor and Carp. the Crud oils were compared with vegetable oil (olive oil) and animal fat (tial fat mutton).
The extracted oil from fresh complete fishs with compared oils intraed on pharmacological system through packed in capsul with and with out garlic`s extract. this system analysis with chemical tests.
Results were analyzed statistically by using the SPSS program with using (CRD)

This study was conducted on Lake Hamrin situated in Diyala governorate, focal Iraq, between latitudes 44^º 53ʹ 26.16 '- 45º 07 ʹ 28.03^ʺ and 34º 04ʹ 24.75^ʺ ــ 34º 19ʹ 12.74^ʺ . As in this study, the surface area of Hamrin Lake was calculated from satellite images during the period from October 2019 to September 2020, with an average satellite image for each month, furthermore,by utilizing the Normalized Differences Water Index (NDWI), the largest surface area was 264,617 km² for October and the lowest surface area 140.202 km² for September. The surface temperature of the lake water was also calculated from satellite images of the Landsat 8 satellite, based on ban

The purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals