This paper considers and proposes new estimators that depend on the sample and on prior information in the case that they either are equally or are not equally important in the model. The prior information is described as linear stochastic restrictions. We study the properties and the performances of these estimators compared to other common estimators using the mean squared error as a criterion for the goodness of fit. A numerical example and a simulation study are proposed to explain the performance of the estimators.
These days, it is crucial to discern between different types of human behavior, and artificial intelligence techniques play a big part in that. The characteristics of the feedforward artificial neural network (FANN) algorithm and the genetic algorithm have been combined to create an important working mechanism that aids in this field. The proposed system can be used for essential tasks in life, such as analysis, automation, control, recognition, and other tasks. Crossover and mutation are the two primary mechanisms used by the genetic algorithm in the proposed system to replace the back propagation process in ANN. While the feedforward artificial neural network technique is focused on input processing, this should be based on the proce
... Show MoreIn this paper, wavelets were used to study the multivariate fractional Brownian motion through the deviations of the random process to find an efficient estimation of Hurst exponent. The results of simulations experiments were shown that the performance of the proposed estimator was efficient. The estimation process was made by taking advantage of the detail coefficients stationarity from the wavelet transform, as the variance of this coefficient showed the power-low behavior. We use two wavelet filters (Haar and db5) to manage minimizing the mean square error of the model.
<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c
... Show MoreABSTRACTBackground: cochlear implants are electronic devices that convert sound energy into electrical signals to stimulate ganglion cells and cochlear nerve fibers. These devices are indicated for patients with severe to profound sensorineural hearing losses who receive little or no benefit from hearing aids. The implant basically takes over the function of the cochlear hair cells. The implant consists of external components (microphone, speech processor and transmitting coil) and internal components (receiver stimulator and electrode array). The implant is inserted via a trans mastoid facial recess approach to the round window and scala tympani.Objectives: to determine the effectiveness and safety of non fixation method in cochlear imp
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This research aim to overcome the problem of dimensionality by using the methods of non-linear regression, which reduces the root of the average square error (RMSE), and is called the method of projection pursuit regression (PPR), which is one of the methods for reducing dimensions that work to overcome the problem of dimensionality (curse of dimensionality), The (PPR) method is a statistical technique that deals with finding the most important projections in multi-dimensional data , and With each finding projection , the data is reduced by linear compounds overall the projection. The process repeated to produce good projections until the best projections are obtained. The main idea of the PPR is to model
... Show MoreA new Schiff base ligand [L] [3-methyl-9,10 phenyl -6,7 dihydro-5,8 –dioxo-1,2 diazo –cyclo dodecu 2,11-diene ,4-one ] and its complexes with (Co(II), Ni(II), Cu (II), Zn(II) and Cd(II)) were synthesis.This ligand was prepared in three steps, in the first step a solution of salicyladehyed in methanol reacted under refluxed with hydrazine monohydrate to give an (intermediate compound 1) which reacted in the second step with sodium pyruvate to give an (intermediate compound 2) which gave the ligand [L] in the three step when it reacted with 1,2- dichloro ethane.The complexes were synthesized by direct reaction of the corresponding metal chloride with the ligand. The ligand and complexes were characterized by spectroscopic methods [IR, UV-
... Show MoreThe influence of pre- shot peening and welding parameters on mechanical and metallurgical properties of dissimilar and similar aluminum alloys AA2024-T3 and AA6061-T6 joints using friction stir welding have been studied. In this work, numbers of plates were equipped from sheet alloys in dimensions (150*50*6) mm then some of them were exposed to shot peening process before friction stir welding using steel ball having diameter 1.25 mm for period of 15 minutes. FSW joints were manufactured from plates at three welding speeds (28, 40, 56 mm/min) and welding speed 40mm/min was chosen at a rotating speed of 1400 rpm for welding the dissimilar pre- shot plates. Tow joints were made at rotational speed of 1000 rpm and welding speed of 40m/min f
... Show MoreThe current research involves psychological pressure (educational,environment andemotionly) for secondary level to 2013-2014.This research includes comparison among students who are trained and not trained in physical education .The sample is(126) students from each gender from first education.Al-Karkh and the research found out that physical education has an effect in lessing emotional and educational in a big degree in student in secondary which affect them positively in their study. &n
... Show MoreGenerally, direct measurement of soil compression index (Cc) is expensive and time-consuming. To save time and effort, indirect methods to obtain Cc may be an inexpensive option. Usually, the indirect methods are based on a correlation between some easier measuring descriptive variables such as liquid limit, soil density, and natural water content. This study used the ANFIS and regression methods to obtain Cc indirectly. To achieve the aim of this investigation, 177 undisturbed samples were collected from the cohesive soil in Sulaymaniyah Governorate in Iraq. Results of this study indicated that ANFIS models over-performed the Regression method in estimating Cc with R2 of 0.66 and 0.48 for both ANFIS and Regre
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