The estimation of the parameters of linear regression is based on the usual Least Square method, as this method is based on the estimation of several basic assumptions. Therefore, the accuracy of estimating the parameters of the model depends on the validity of these hypotheses. The most successful technique was the robust estimation method which is minimizing maximum likelihood estimator (MM-estimator) that proved its efficiency in this purpose. However, the use of the model becomes unrealistic and one of these assumptions is the uniformity of the variance and the normal distribution of the error. These assumptions are not achievable in the case of studying a specific problem that may include complex data of more than one model. To deal with this type of problem, a mixture of linear regression is used to model such data. In this article, we propose a genetic algorithm-based method combined with (MM-estimator), which is called in this article (RobGA), to improve the accuracy of the estimation in the final stage. We compare the suggested method with robust bi-square (MixBi) in terms of their application to real data representing blood sample. The results showed that RobGA is more efficient in estimating the parameters of the model than the MixBi method with respect to mean square error (MSE) and classification error (CE).
This research is concerned with the re-analysis of optical data (the imaginary part of the dielectric function as a function of photon energy E) of a-Si:H films prepared by Jackson et al. and Ferlauto et al. through using nonlinear regression fitting we estimated the optical energy gap and the deviation from the Tauc model by considering the parameter of energy photon-dependence of the momentum matrix element of the p as a free parameter by assuming that density of states distribution to be a square root function. It is observed for films prepared by Jackson et al. that the value of the parameter p for the photon energy range is is close to the value assumed by the Cody model and the optical gap energy is which is also close to the value
... Show MoreThe present study aimed to determine the genetic divergence of seven maize genotypes (Al-Maha, Sumer, Al-Fajr, Baghdad, 5018, 4 × 1 single hybrid, and 4 × 2 single hybrid) under two varied levels of nitrogen fertilization (92 and 276 kg N ha-1). The experiment occurred in 2022 in a randomized complete block design (RCBD) with a split-plot arrangement and three replications at the College of Agricultural Engineering Sciences, University of Baghdad, Iraq. The nitrogen fertilization levels served as main plots, with the maize genotypes allocated as the subplots. The results revealed that genetic variance was higher than the environmental variance for most traits, and the coefficient of phenotypic variation was close to the genetic va
... Show MoreIn this study, the quality assurance of the linear accelerator available at the Baghdad Center for Radiation Therapy and Nuclear Medicine was verified using Star Track and Perspex. The study was established from August to December 2018. This study showed that there was an acceptable variation in the dose output of the linear accelerator. This variation was ±2% and it was within the permissible range according to the recommendations of the manufacturer of the accelerator (Elkta).
: In this study, a linear synchronous machine is compared with a linear transverse flux machine. Both machines have been designed and built with the intention of being used as the power take off in a free piston engine. As both topologies are cylindrical, it is not possible to construct either using just flat laminations and so alternative methods are described and demonstrated. Despite the difference in topology and specification, the machines are compared on a common base in terms of rated force and suitability for use as a generator. Experience gained during the manufacture of two prototypes is described.
Linear Feedback Shift Register (LFSR) systems are used widely in stream cipher systems field. Any system of LFSR's which wauldn't be attacked must first construct the system of linear equations of the LFSR unit. In this paper methods are developed to construct a system of linear/nonlinear equations of key generator (a LFSR's system) where the effect of combining (Boolean) function of LFSR is obvious. Before solving the system of linear/nonlinear equations by using one of the known classical methods, we have to test the uniqueness of the solution. Finding the solution to these systems mean finding the initial values of the LFSR's of the generator. Two known generators are used to test and apply the ideas of the paper,
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Abstract
The Classical Normal Linear Regression Model Based on Several hypotheses, one of them is Heteroscedasticity as it is known that the wing of least squares method (OLS), under the existence of these two problems make the estimators, lose their desirable properties, in addition the statistical inference becomes unaccepted table. According that we put tow alternative, the first one is (Generalized Least Square) Which is denoted by (GLS), and the second alternative is to (Robust covariance matrix estimation) the estimated parameters method(OLS), and that the way (GLS) method neat and certified, if the capabilities (Efficient) and the statistical inference Thread on the basis of an acceptable
... Show MoreThe study hypothesize that the majority of Arab countries show a poor agricultural economic efficiency which resulted in a weak productive capacity of wheat in the face of the demand, which in turn led to the fluctuation of the rate of self-sufficiency and thus increase the size of the food gap. The study aims at estimating and analyzing the food security indicators for their importance in shaping the Arabic agricultural policy, which aims to achieve food security through domestic production and reduce the import of food to less possible extent. Some of the most important results reached by the study were that the increase in the amount of consumption of wheat in the countries of t
... Show MoreExploring the B-Spline Transform for Estimating Lévy Process Parameters: Applications in Finance and Biomodeling Exploring the B-Spline Transform for Estimating Lévy Process Parameters: Applications in Finance and Biomodeling Letters in Biomathematics · Jul 7, 2025Letters in Biomathematics · Jul 7, 2025 Show publication This paper, presents the application of the B-spline transform as an effective and precise technique for estimating key parameters i.e., drift, volatility, and jump intensity for Lévy processes. Lévy processes are powerful tools for representing phenomena with continuous trends with abrupt changes. The proposed approach is validated through a simulated biological case study on animal migration in which movements are mo
... Show MoreEnvironmental factors that damage plant cells by dehydrating them, such cold, drought, and high salinity, are the most common environmental stresses that have an impact on plant growth, development, and productivity in cultivated regions around the world. Several types of plants have several drought, salinity, and cold inducible genes that make them tolerant to environmental challenges. The purpose of this study was to investigate several species in
DBNRSK Sayed, Journal of Strategic Research in Social Science (JoSReSS), 2020