This paper presents a hybrid genetic algorithm (hGA) for optimizing the maximum likelihood function ln(L(phi(1),theta(1)))of the mixed model ARMA(1,1). The presented hybrid genetic algorithm (hGA) couples two processes: the canonical genetic algorithm (cGA) composed of three main steps: selection, local recombination and mutation, with the local search algorithm represent by steepest descent algorithm (sDA) which is defined by three basic parameters: frequency, probability, and number of local search iterations. The experimental design is based on simulating the cGA, hGA, and sDA algorithms with different values of model parameters, and sample size(n). The study contains comparison among these algorithms depending on MSE value. One can conc

The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

The aim of the present study is to identify the level of prosoical behavior of Baghdad University's students and to recognize the differences between male and female students. Moreover, it also aims to identify the level of openness to experience for these students. A random sample of (123) students has been selected; 77 males and 46 females. Two scales have been used in the study. The Prosocialness scale for adults by Caprara. Et al (2005) has been translated into the Arabic language and relies on four types of actions (Helping, Sharing, Taking care, and feeling Empathetic with others) and the other scale is the Openness to Experience Scale, which is one of the Big Five Inventory by John and Srivastava (1999). The main results showed a

This search concerns study the crack growth in the wall of pipes made of low carbon steel under the impact load and using the effect of moisture (rate of moisture 50%). The environmental conditions were controlled using high accuracy digital control with sensors. The pipe has a crack already. The test was performed and on two type of specimens, one has a length of 100cm and other have length 50cm. The results were, when the humidity was applied to the pipe, the crack would enhance to grow (i.e. the number of cycles needed to grow the crack will reduce). In addition, when the test performed on the specimens of length 50cm the number of cycles needed to grow the crack is increased due to the effect of bending stress on the

This research concerns study the crack growth in the wall of pipes made of low carbon steel under the impact load and using the effect of hygrothermal (rate of moisture 50% and 50℃ temperature). The environmental conditions were controlled using high accuracy digital control with sensors. The pipe have a crack already. The test was performed and on two type of specimens, one have length of 100cm and other have length 50cm. The results were, when the humidity was applied to the pipe, the crack would enhance to growth (i.e. the number of cycles needed to growth the crack will reduce). In addition, when the temperature was increase the number of cycles needed to growth the crack are reduced because the effect of heat on the mechanical pro

The goal (purpose) from using development technology that require mathematical procedure related with high Quality & sufficiency of solving complex problem called Dynamic Programming with in recursive method (forward & backward) through  finding series of associated decisions for reliability function of Pareto distribution estimator by using two approach Maximum likelihood & moment .to conclude optimal policy

Rate of penetration plays a vital role in field development process because the drilling operation is expensive and include the cost of equipment and materials used during the penetration of rock and efforts of the crew in order to complete the well without major problems. It’s important to finish the well as soon as possible to reduce the expenditures. So, knowing the rate of penetration in the area that is going to be drilled will help in speculation of the cost and that will lead to optimize drilling outgoings. In this research, an intelligent model was built using artificial intelligence to achieve this goal.  The model was built using adaptive neuro fuzzy inference system to predict the rate of penetration in