In high-dimensional semiparametric regression, balancing accuracy and interpretability often requires combining dimension reduction with variable selection. This study intro- duces two novel methods for dimension reduction in additive partial linear models: (i) minimum average variance estimation (MAVE) combined with the adaptive least abso- lute shrinkage and selection operator (MAVE-ALASSO) and (ii) MAVE with smoothly clipped absolute deviation (MAVE-SCAD). These methods leverage the flexibility of MAVE for sufficient dimension reduction while incorporating adaptive penalties to en- sure sparse and interpretable models. The performance of both methods is evaluated through simulations using the mean squared error and variable selection cri

بهذا البحث نقارن معاييرالمعلومات التقليدية (AIC , SIC, HQ , FPE ) مع معيارمعلومات الانحراف المحور (MDIC) المستعملة لتحديد رتبة انموذج الانحدارالذاتي (AR) للعملية التي تولد البيانات,باستعمال المحاكاة وذلك بتوليد بيانات من عدة نماذج للأنحدارالذاتي,عندما خضوع حد الخطأ للتوزيع الطبيعي بقيم مختلفة لمعلماته

Drip irrigation is one of the conservative irrigation techniques since it implies supplying water directly on the soil through the emitter; it can supply water and fertilizer directly into the root zone. An equation to estimate the wetted area in unsaturated soil is taking into calculating the water absorption by roots is simulated numerically using HYDRUS (2D/3D) software. In this paper, HYDRUS comprises analytical types of the estimate of different soil hydraulic properties. Used one soil type, sandy loam, with three types of crops; (corn, tomato, and sweet sorghum), different drip discharge, different initial soil moisture content was assumed, and different time durations. The relative error for the different hydrauli

The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample

The collected premiums and the compensations paid are among the main variables that have a prominent role in determining the level of financial solvency of insurance companies, as the higher the financial solvency of the insurance company, the more attractive it is to the target audience to acquire the company's insurance services.

Hence the importance of the issue of the solvency of insurance companies, as it is one of the critical matters on which the effectiveness of the insurance company and its continuation in the labor market depend.

In this research, we try to clarify the role of collected premiums and compensations paid in determining the level of operational solvency of t

The research aims to verify the role of the Human Resources Strategic Management (HRSM) in enhancing the strategic success factors for talent (SSFT) in the General Tourism Authority by distributing a questionnaire consisting of (36) paragraphs on an intentional sample represented by the higher departments as it reached (50) and the sample valid for testing was (44) Person and to test the relationships between the two research variables, the researchers used statistical methods represented by (Bartlett test / mean / simple regression coefficient / difference coefficient, alpha- cronbachAch, confirmatory factor Analysis ) through the statistical program (SPSS v.23 & AMOS v.23). In enhancing the factors of success for talent management in the

The research aims to study the basic concepts of the underwriting policy with its various indicators. The researcher studies the underwriting policy with its various indicators (sex, health status, age of the insured, insurance amount, The method of acceptance, payment method, and duration of insurance) where each of these indicators constitute an important factor in the productivity of life insurance policies, where the productivity of life insurance policies face many difficulties because insurance is a service and not a tangible material commodity and its benefits and not current. Therefore, the life insurance company needs to use a prudent underwriting policy so as not to endanger its financial position due to the expansion of the un