The purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals don’t have the serial correlation and ARCH effect, as well as these models, should have a higher value of log-likelihood and SVR-FIGARCH models managed to outperform FIGARCH models with normal and student’s t distributions. The SVR-FIGARCH model exhibited statistical significance and improved accuracy obtained with the SVM technique. Finally, we evaluate the forecasting performance of the various volatility models, and then we choose the best fitting model to forecast the volatility for each series, depending on three forecasting accuracy measures RMSE, MAE, and MAPE.
The Machine learning methods, which are one of the most important branches of promising artificial intelligence, have great importance in all sciences such as engineering, medical, and also recently involved widely in statistical sciences and its various branches, including analysis of survival, as it can be considered a new branch used to estimate the survival and was parallel with parametric, nonparametric and semi-parametric methods that are widely used to estimate survival in statistical research. In this paper, the estimate of survival based on medical images of patients with breast cancer who receive their treatment in Iraqi hospitals was discussed. Three algorithms for feature extraction were explained: The first principal compone
... Show MoreThree hundred Iraqi people participated in demographic and attitudes study about red and white meat consumption. The mean age of the participants was 50 SD ± 11 years (mean 30-72); 51% were females and 49% males, mostly in forties who lived ≥ 5 years in Baghdad. The results showed that 80% of individuals prefer red meat. A 90% of people prefer fresh meat compared to frozen and processed meat. A 60% of people buy meat from popular markets. Nearly 87% of respondents believe the improving of livestock sector is essential and 80% of people confirmed there are obstacles to development this sector. An 80% of participates thought the reasons of the high prices of local fresh meat is the lack of planning and support to livestock sector. A survey
... Show MoreEpilepsy is the most common neurological disorder after Alzheimer and other cerebrovascular diseases. Antiepileptic drugs (AED's) are one of the most important methods to prevent epileptic seizers. Antiepileptic drugs can cause damage to the liver which is the largest and most important glandular organ in the body with many other drugs. Carbamazepine (CBZ) is a known anticonvulsant that is widely used and known for a decade, it was used to treat trigeminal neuralgia, bipolar disorder and epilepsy and it can cause hepatotoxicity. In this study female white mice received CBZ suspension at a dose of 20 mg/kg/mouse via gastric gavage for 30 days, tissue samples were collected for scanning electron microscopy. We observed the adverse effects of
... Show MoreReconstruction of female identity is one of the important issues in modern times. The majority of the females who descent from the countries of the third world confront lots of problems because of their race and gender. Black females or colored skin females because of the oppression of the white society upon them, try hard to cope with society in order to get some relief and feel that they are part of this cruel white society. One of the solutions for these black females is to reconstruct their identity by mimicry to the English beauty standards. Zadie Smith is a postcolonial author. She deals with third- world women and how they are treated in a minority and in a racist way. She strives to empower the subaltern black females who ha
... Show MoreThe current paper proposes a new estimator for the linear regression model parameters under Big Data circumstances. From the diversity of Big Data variables comes many challenges that can be interesting to the researchers who try their best to find new and novel methods to estimate the parameters of linear regression model. Data has been collected by Central Statistical Organization IRAQ, and the child labor in Iraq has been chosen as data. Child labor is the most vital phenomena that both society and education are suffering from and it affects the future of our next generation. Two methods have been selected to estimate the parameter
... Show MoreIn this paper, we propose a method using continuous wavelets to study the multivariate fractional Brownian motion through the deviations of the transformed random process to find an efficient estimate of Hurst exponent using eigenvalue regression of the covariance matrix. The results of simulations experiments shown that the performance of the proposed estimator was efficient in bias but the variance get increase as signal change from short to long memory the MASE increase relatively. The estimation process was made by calculating the eigenvalues for the variance-covariance matrix of Meyer’s continuous wavelet details coefficients.
In this paper, we propose a method using continuous wavelets to study the multivariate fractional Brownian motion through the deviations of the transformed random process to find an efficient estimate of Hurst exponent using eigenvalue regression of the covariance matrix. The results of simulations experiments shown that the performance of the proposed estimator was efficient in bias but the variance get increase as signal change from short to long memory the MASE increase relatively. The estimation process was made by calculating the eigenvalues for the variance-covariance matrix of Meyer’s continuous wavelet details coefficients.
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
... Show MoreIn this study, gamma-ray spectrometry with an HPGe detector was used to measure the specific activity concentrations of 226Ra, 232Th, and 40K in soil samples collected from IT1 oil reservoirs in Kirkuk city, northeast Iraq. The “spectral line Gp” gamma analysis software package was used to analyze the spectral data. 226Ra specific activity varies from 9 0.34 Bq.kg-1 to 17 0.47 Bq.kg-1. 232Th specific activity varies from 6.2 0.08 Bq.kg-1 to 18 0.2 Bq.kg-1. 40K specific activity varies from 25 0.19 Bq.kg-1 to 118 0.41 Bq.kg-1. The radiological hazard due to the radiation emitted from natural r
... Show MoreGas-lift technique plays an important role in sustaining oil production, especially from a mature field when the reservoirs’ natural energy becomes insufficient. However, optimally allocation of the gas injection rate in a large field through its gas-lift network system towards maximization of oil production rate is a challenging task. The conventional gas-lift optimization problems may become inefficient and incapable of modelling the gas-lift optimization in a large network system with problems associated with multi-objective, multi-constrained, and limited gas injection rate. The key objective of this study is to assess the feasibility of utilizing the Genetic Algorithm (GA) technique to optimize t