This research deals with a shrinking method concernes with the principal components similar to that one which used in the multiple regression “Least Absolute Shrinkage and Selection: LASS”. The goal here is to make an uncorrelated linear combinations from only a subset of explanatory variables that may have a multicollinearity problem instead taking the whole number say, (K) of them. This shrinkage will force some coefficients to equal zero, after making some restriction on them by some "tuning parameter" say, (t) which balances the bias and variance amount from side, and doesn't exceed the acceptable percent explained variance of these components. This had been shown by MSE criterion in the regression case and the percent explained variance in the principal components case.
In this paper we proposed a new method for selecting a smoothing parameter in kernel estimator to estimate a nonparametric regression function in the presence of missing values. The proposed method is based on work on the golden ratio and Surah AL-E-Imran in the Qur'an. Simulation experiments were conducted to study a small sample behavior. The results proved the superiority the proposed on the competition method for selecting smoothing parameter.
in this paper the collocation method will be solve ordinary differential equations of retarted arguments also some examples are presented in order to illustrate this approach
Research summarized in applying the model of fuzzy goal programming for aggregate production planning , in General Company for hydraulic industries / plastic factory to get an optimal production plan trying to cope with the impact that fluctuations in demand and employs all available resources using two strategies where they are available inventories strategy and the strategy of change in the level of the workforce, these strategies costs are usually imprecise/fuzzy. The plant administration trying to minimize total production costs, minimize carrying costs and minimize changes in labour levels. depending on the gained data from th
... Show MoreThe Ant System Algorithm (ASA) is a member of the ant colony algorithms family in swarm intelligence methods (part of the Artificial Intelligence field), which is based on the behavior of ants seeking a path and a source of food in their colonies. The aim of This algorithm is to search for an optimal solution for Combinational Optimization Problems (COP) for which is extremely difficult to find solution using the classical methods like linear and non-linear programming methods.
The Ant System Algorithm was used in the management of water resources field in Iraq, specifically for Haditha dam which is one of the most important dams in Iraq. The target is to find out an efficient management system for
... Show MoreThis work is devoted to define new generalized gamma and beta functions involving the recently suggested seven-parameter Mittag-Leffler function, followed by a review of all related special cases. In addition, necessary investigations are affirmed for the new generalized beta function, including, Mellin transform, differential formulas, integral representations, and essential summation relations. Furthermore, crucial statistical application has been realized for the new generalized beta function.
Seeds of five cultivars of oats (Avena sativa) were introduced from Italy in 2009. Seeds were propagated on the farm of the Dept. of Field Crops Sci. / Coll. of Agric. / Univ. of Baghdad in the season 2009 – 2010. The cultivars Anatolia, Alguda, Hamel, Pimula and Genzania were planted under 3 irrigation intervals; 3, 4 and 5 weeks to give water depth of 480, 400 and 320 mm, respectively . The depth of water was 80 mm each irrigation. A factorial experiment with RCBD of 4 replicates was conducted in 2 consecutive seasons in 2010 – 2011 and 2011 – 2012. The cultivar Alguda gave highest grain yield (8.07 t/ ha) under 480 mm, and 7.02 t / ha average of 3 water depths. This cultivar was characterized by high growth rate (13.2 g/m2/ d) that
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Much attention has been paid for the use of robot arm in various applications. Therefore, the optimal path finding has a significant role to upgrade and guide the arm movement. The essential function of path planning is to create a path that satisfies the aims of motion including, averting obstacles collision, reducing time interval, decreasing the path traveling cost and satisfying the kinematics constraints. In this paper, the free Cartesian space map of 2-DOF arm is constructed to attain the joints variable at each point without collision. The D*algorithm and Euclidean distance are applied to obtain the exact and estimated distances to the goal respectively. The modified Particle Swarm Optimization al
... Show MoreA new modified differential evolution algorithm DE-BEA, is proposed to improve the reliability of the standard DE/current-to-rand/1/bin by implementing a new mutation scheme inspired by the bacterial evolutionary algorithm (BEA). The crossover and the selection schemes of the DE method are also modified to fit the new DE-BEA mechanism. The new scheme diversifies the population by applying to all the individuals a segment based scheme that generates multiple copies (clones) from each individual one-by-one and applies the BEA segment-wise mechanism. These new steps are embedded in the DE/current-to-rand/bin scheme. The performance of the new algorithm has been compared with several DE variants over eighteen benchmark functions including sever
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