The contemporary business environment is witnessing increasing calls for modifications to the traditional cost system, and a trend towards adopting cost management techniques to provide appropriate financial and non-financial information for senior and executive departments, including the Resource Consumption Accounting (RCA) technique in question, which classifies costs into fixed and variable to support the decision-making process. Moreover, (RCA) combines two approaches to cost estimation, the first based on activity-based cost accounting (ABC) and the second on the German cost accounting method (GPK). The research aims to provide a conceptual vision for resource consumption accounting, after Considering it as an accounting te

     The objective of the study is to demonstrate the predictive ability is better between the logistic regression model and Linear Discriminant function using the original data first and then the Home vehicles to reduce the dimensions of the variables for data and socio-economic survey of the family to the province of Baghdad in 2012 and included a sample of 615 observation with 13 variable, 12 of them is an explanatory variable and the depended variable is number of workers and the unemployed.

     Was conducted to compare the two methods above and it became clear by comparing the  logistic regression model best of a Linear Discriminant  function written

This study is concerned with the comparison of the results of some tests of passing and dribbling of the basketball of tow different years between teams of chosen young players in Baghdad. Calculative methods were used namely (Arithmetic mean, Value digression and T.test for incompatible specimens). After careful calculative treatments, it has been that there were abstract or no abstract differences in the find results of chestpass, highdribble and cross-over dribble. The clubs were: (Al-Khark, Air defence, Police and Al-Adamiyah) each one separate from the other for the year (2000-2001). After all that many findings were reached such as the lack of objective valuation (periodical tests) between one sport season and the other. In the light

Among the metaheuristic algorithms, population-based algorithms are an explorative search algorithm superior to the local search algorithm in terms of exploring the search space to find globally optimal solutions. However, the primary downside of such algorithms is their low exploitative capability, which prevents the expansion of the search space neighborhood for more optimal solutions. The firefly algorithm (FA) is a population-based algorithm that has been widely used in clustering problems. However, FA is limited in terms of its premature convergence when no neighborhood search strategies are employed to improve the quality of clustering solutions in the neighborhood region and exploring the global regions in the search space. On the

Support vector machine (SVM) is a popular supervised learning algorithm based on margin maximization. It has a high training cost and does not scale well to a large number of data points. We propose a multiresolution algorithm MRH-SVM that trains SVM on a hierarchical data aggregation structure, which also serves as a common data input to other learning algorithms. The proposed algorithm learns SVM models using high-level data aggregates and only visits data aggregates at more detailed levels where support vectors reside. In addition to performance improvements, the algorithm has advantages such as the ability to handle data streams and datasets with imbalanced classes. Experimental results show significant performance improvements in compa