المستخلص يهدف هذا البحث الى تجاوز مشكلة البعدية من خلال طرائق الانحدار اللامعلمي والتي تعمل على تقليل جذر متوسط الخطأ التربيعي (RMSE) , أذ تم  استعمال طريقة انحدار الاسقاطات المتلاحقة  (PPR)    ,والتي تعتبر احدى طرائق اختزال الابعاد التي تعمل على تجاوز مشكلة البعدية (curse of dimensionality) , وان طريقة (PPR) من التقنيات الاحصائية التي تهتم بأيجاد الاسقاطات الاكثر أهمية في البيانات المتعددة الابعاد , ومع ايجاد كل اسقاط

كتاب المنهجية الحديثة في التخطيط والتدريب بكرة القدم أ.د. موفق مجيد المولى أ.د. جبار رحيمة أ.د. فاطمة عبد مالح كتاب (( المنهجية الحديثة في التخطيط والتدريب بكرة القدم )) تأليف د. موفق مجيد المولى ود. جبار رحيمة الكعبي ود. فاطمة عبد البصري تناول فيه العديد من الموضوعات العلمية الحديثة بكرة القدم

Supply Chain Management (SCM) attempts to a create a synchronization of the firm’s processes and those of the supplier to match the flow of materials, services, and information with the customer demand. Due to its importance, the SCM has become inevitable to modern companies. Therefore this research work has been conducted to set a theoretical and applied basis to assist the 1 AYAR factory in adopting the Electronic Supply Chain (e-SC).  To accomplish that the searchers applied many tools such as: quantitative and qualitative analysis, process analysis, Visual Basic software, Monte Carlo Simulation to simulation the designed supply chain to compare its performance against the actual performance of the current supply chain

تعد البرمجة الخطية عاملاً مؤثراً وفعالاً في عملية صنع و إتخاذ القرار عندما تكون الموارد متاحة أو متوفرة لكي تعطي أهدافاً معينة ، وتكمن البرمجة الخطية في حل وتقييم الانشطة أو الفعاليات عند تطبيق إحدى أدواتها وهي الطريقة المبسطة العامة ، التي يكون فيها الحل مقبولاً (ممكناً) ويجب التوصل الى الحل الامثل عندها تسمى بالطريقة المبسطة الاولية أو يكون الحل فيها أمثلاً ويجب التوصل الى الحل الم

The goal beyond this Research is to review methods that used to estimate Logistic distribution parameters. An exact estimators method which is the Moment method, compared with other approximate estimators obtained essentially from White approach such as: OLS, Ridge, and Adjusted Ridge as a suggested one to be applied with this distribution. The Results of all those methods are based on Simulation experiment, with different models and variety of  sample sizes. The comparison had been made with respect to two criteria: Mean Square Error (MSE) and Mean Absolute Percentage Error (MAPE).  

The aim of this paper is to estimate a nonlinear regression function of the Export of the crude oil Saudi (in Million Barrels) as a function of the number of discovered fields.

 Through studying the behavior of the data we show that its behavior was not followed a linear pattern or can put it in a known form so far there was no possibility to see a general trend resulting from such exports.

We use different nonlinear estimators to estimate a regression function, Local linear estimator, Semi-parametric as well as an artificial neural network estimator (ANN).

The results proved that the (ANN) estimator is the best nonlinear estimator am

In this study, we review the ARIMA (p, d, q), the EWMA and the DLM (dynamic linear moodelling) procedures in brief in order to accomdate the ac(autocorrelation)  structure of data .We consider the recursive estimation and prediction algorithms based on Bayes and KF (Kalman filtering) techniques for correlated observations.We investigate the effect on the MSE of  these procedures and compare them using generated data.

Because of the experience of the mixture problem of high correlation and the existence of linear MultiCollinearity between the explanatory variables, because of the constraint of the unit and the interactions between them in the model, which increases the existence of links between the explanatory variables and this is illustrated by the variance inflation vector (VIF), L-Pseudo component to reduce the bond between the components of the mixture.

    To estimate the parameters of the mixture model, we used in our research the use of methods that increase bias and reduce variance, such as the Ridge Regression Method and the Least Absolute Shrinkage and Selection Operator (LASSO) method a