Recently Genetic Algorithms (GAs) have frequently been used for optimizing the solution of estimation problems. One of the main advantages of using these techniques is that they require no knowledge or gradient information about the response surface. The poor behavior of genetic algorithms in some problems, sometimes attributed to design operators, has led to the development of other types of algorithms. One such class of these algorithms is compact Genetic Algorithm (cGA), it dramatically reduces the number of bits reqyuired to store the poulation and has a faster convergence speed. In this paper compact Genetic Algorithm is used to optimize the maximum likelihood estimator of the first order moving avergae model MA(1). Simulation results based on MSE were compared with those obtained from the moments method and showed that the Canonical GA and compact GA can give good estimator of θ for the MA(1) model. Another comparison has been conducted to show that the cGA method has less number of function evaluations, minimum searched space percentage, faster convergence speed and has a higher optimal precision than that of the Canonical GA.
A series of laboratory model tests has been carried out to investigate the using of pomegranate sticks mat as reinforcement to increase the bearing capacity of footing on loose sand. The influence of depth and length of pomegranate sticks layer was examined. In the present research single layer of pomegranate sticks reinforcement was used to strengthen the loose sand stratum beneath the strip footing. The dimensions of the used foundation were 4*20 cm. The reinforcement layer has been embedded at depth 2, 4 and 8 cm under surcharge stresses . Reinforcing layer with length of 8 and 16 cm were used. The final model test results indicated that the inclusion of pomegranate sticks reinforcement is very effective in improvement the loading cap
... Show MoreFollowing model educational offenders in collection and Alasbaka of fifth grade students preparatory in history A. M. Dr Prepared by: Dr. Bashaer Mawloud Tawfeeq, The Center of Educational and Psychological Studies Baghdad University - There is no difference statistically significant at the 0.05 level of significance between the average scores of the following students studying using model and offenders and who are studying in the usual manner (traditional) in the collection - There is no difference statistically significant at the 0.05 level of significance between the mean scores for the following students studying using model and offenders and who are studying in the usual manner (traditional) in retention Find limits: Current search
... Show MoreThe effect of superficial gas velocity within the range 0.01-0.164 m/s on gas holdup (overall, riser and down comer), volumetric oxygen mass transfer coefficient, liquid circulation velocity was studied in an internal loop concentric tubes airlift reactor (working volume 45 liters). It was shown that as the usg increases the gas holdup and also the liquid circulation velocity increase. Also it was found that increasing superficial gas velocity lead to increase the interfacial area that increases the overall oxygen mass transfer coefficient. The hydrodynamic experimental results were modeled with the available equations in the literature. The predicted data gave an acceptable accuracy with the empirical data.
The final
... Show MoreThe theme of this Study presents analysis and discuss to the "Share the framework for assessing inflation," a practical study in a sample of joint stock companies listed on the Iraq Stock Exchange for the years (2009-2013). To determine the extent of the disparity between the nominal value of shares (Nominal Value) before deducting inflation and the real value (Real Value) per share, after deducting inflation in the case of zero growth. The study relied on annual reports of the companies of the research sample of the Iraq Stock Exchange, as well as the Iraqi Securities Commission. Besides the annual reports issued by the Ministry of Planning, as well as annual reports and statistical bulletin issued by the Central Bank of Iraq. It is fra
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
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