Background Due to the intermittent, nonlinear, and uncertain behavior of renewable energy sources (res) such as solar and wind, grid stability and reliability require very high forecasting and optimization skills as widely reported in the literature. Traditional optimization methods work very well in small or static systems but are suffer difficulty on large-scale, dynamic and stochastic renewable environment due to their NP-hard nature. Methods The framework introduces the concept of a Machine Learning-Assisted Hybrid Cuckoo Search (ML-HCS) that combines CS with a hybrid metaheuristic and integrates Long Short-Term Memory (LSTM) networks for forecasting based on both regression models of LSTMs and hybrid optimization algorithm

The temperature distributions are to be evaluated for the furnace of Al-Mussaib power plant. Monte Carlo simulation procedure is used to evaluate the radiation heat transfer inside the furnace, where the radiative transfer is the most important process occurring there. Weighted sum of gray-gases model is used to evaluate the radiative properties of the non gray gas in the enclosure. The energy balance equations are applied for each gas, and surface zones, and by solving these equations, both the temperature, and the heat flux are found.

   Good degree of accuracy has been obtained, when comparing the results obtained by the simulation with the data of the designing company, and the data obtained by the zonal method. In

The objective of this research work is to evaluate the quality of central concrete plant of Al-Rasheed Company by using Six Sigma approach which is a measure of quality that strives for near elimination of defects using the statistical methods to improve outputs that are critical to customers. The fundamental objective of Six Sigma methodology is the implementation of a measurement-based strategy that focuses on process improvement and variation reduction to reach delighting customers, and then suggesting an improvement system to improve the production of concrete in Al-Rasheed State Contracting Construction Company.
A field survey includes two parts (open and close questionnaire) that aimed to get the data and information required f

Abstract

   The aim of this research is to concentrate on the of knowledge management activities, initial activities: (Acquisition, Selection, Generation, Assimilation, Emission) knowledge, and support activities: (Measurement, Control, Coordination, Leadership) that is manipulate and controlling in achieving knowledge management cases in organization, that’s is leads to  knowledge chain model, then determining the level of membership for these activities to knowledge chain model in a sample of Iraqi organization pushed by knowledge (Universities). The research depends on check list for gaining the data required, theses check list designed by apparently  in diagnosing research dimensions and measurem

In present work the effort has been put in finding the most suitable color model for the application of information hiding in color images. We test the most commonly used color models; RGB, YIQ, YUV, YCbCr1 and YCbCr2. The same procedures of embedding, detection and evaluation were applied to find which color model is most appropriate for information hiding. The new in this work, we take into consideration the value of errors that generated during transformations among color models. The results show YUV and YIQ color models are the best for information hiding in color images.

The Mauddud reservoir, Khabaz oil field which is considered one of the main carbonate reservoirs in the north of Iraq. Recognizing carbonate reservoirs represents challenges to engineers because reservoirs almost tend to be tight and overall heterogeneous. The current study concerns with geological modeling of the reservoir is an oil-bearing with the original gas cap. The geological model is establishing for the reservoir by identifying the facies and evaluating the petrophysical properties of this complex reservoir, and calculate the amount of hydrocarbon. When completed the processing of data by IP interactive petrophysics software, and the permeability of a reservoir was calculated using the concept of hydraulic units then, there

Spatial Autoregressive Model (SAR) is one of the modeling frameworks that indicates a spatial dependence in the response variable. SAR model has a weakness, which is represented by the unknown variance of the residuals. Therefore, an alternative model has used titled Spatial Autoregressive Quantile Regression (SARQR) model That which is obtained by combining SAR and Quantile Regression (QR) models, is a regression method with the approach of dividing the data into particular quantiles that are likely to have different estimate values. This alternative model addresses the variance issues in SAR models. Additionally, the SARQR model not only resolves the issue of spatial variance but also serves as a solution for dealing with non-normal data