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 paper discussed the solution of an equivalent circuit of solar cell, where a single diode model is presented. The nonlinear equation of this model has suggested and analyzed an iterative algorithm, which work well for this equation with a suitable initial value for the iterative. The convergence of the proposed method is discussed. It is established that the algorithm has convergence of order six. The proposed algorithm is achieved with a various values of load resistance. Equation by means of equivalent circuit of a solar cell so all the determinations is achieved using Matlab in ambient temperature. The obtained results of this new method are given and the absolute errors is demonstrated.
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.
The increasing efficiency of the telecommunications network in the city contributes to the increase in spatial interaction between activities (to influence and mutual influence) This study is based on the idea that the upgrading of telephone services provided to citizens are done exclusively through the growth and development of all levels of the service using advanced technologies to know the problems and appropriate solutions in short time and less cost. Thus, crystallized the objectives of the study which was built for the importance of GIS in the planning of services in general, and infrastructure services, in particular, including telephone services, which is represent a point of contact between individuals on the one hand a
... Show MoreThis research aims to review the importance of estimating the nonparametric regression function using so-called Canonical Kernel which depends on re-scale the smoothing parameter, which has a large and important role in Kernel and give the sound amount of smoothing .
We has been shown the importance of this method through the application of these concepts on real data refer to international exchange rates to the U.S. dollar against the Japanese yen for the period from January 2007 to March 2010. The results demonstrated preference the nonparametric estimator with Gaussian on the other nonparametric and parametric regression estima
... Show MoreDue to its importance in physics and applied mathematics, the non-linear Sturm-Liouville problems
witnessed massive attention since 1960. A powerful Mathematical technique called the Newton-Kantorovich
method is applied in this work to one of the non-linear Sturm-Liouville problems. To the best of the authors’
knowledge, this technique of Newton-Kantorovich has never been applied before to solve the non-linear
Sturm-Liouville problems under consideration. Accordingly, the purpose of this work is to show that this
important specific kind of non-linear Sturm-Liouville differential equations problems can be solved by
applying the well-known Newton-Kantorovich method. Also, to show the efficiency of appl
This research dealt with the analysis of murder crime data in Iraq in its temporal and spatial dimensions, then it focused on building a new model with an algorithm that combines the characteristics associated with time and spatial series so that this model can predict more accurately than other models by comparing them with this model, which we called the Combined Regression model (CR), which consists of merging two models, the time series regression model with the spatial regression model, and making them one model that can analyze data in its temporal and spatial dimensions. Several models were used for comparison with the integrated model, namely Multiple Linear Regression (MLR), Decision Tree Regression (DTR), Random Forest Reg
... Show MoreThis research is to take advantage of the performance capabilities which the piano has become famous with and transfer the impact of that advantage to the possibilities of playing the violin. The research aims to introduce the effect of using the piano on the development of the violinists' musical potential. The research, in its literature, focuses on the interpretation of the impact on the possibility of both instruments (piano and violin) in two main sections: the piano (its origin, potential and role in music) and the violin (its origin, potential and role in music). The procedures of the research consisted of presenting a special analysis of a questionnaire consisting of a number of questions presented by the researcher to her resear
... Show MoreIn this paper, the finite element method is used to study the dynamic behavior of the damaged rotating composite blade. Three dimensional, finite element programs were developed using a nine node laminated shell as a discretization element for the blade structure (the same element type is used for damaged and non-damaged structure). In this analysis the initial stress effect (geometric stiffness) and other rotational effects except the carioles acceleration effect are included. The investigation covers the effect speed of rotation, aspect ratio, skew angle, pre-twist angle, radius to length, layer lamination and fiber orientation of composite blade. After modeling a non-damaged rotating composite blade, the work procedure was to ap
... Show MoreThe gypseous soil may be one of the problems that face the engineers especially when it used as a foundation for hydraulic structures, roads, and other structures. Gypseous soil is strong soil and has good properties when it is dry, but the problem arises when building hydraulic installations or heavy buildings on this soil after wetting the water to the soil by raising the water table level from any source or from rainfall which leads to dissolve the gypsum content.
Cement-stabilized soil has been successfully used as a facing or lining for earth channel, highway embankments and drainage ditches to reduce the risk of erosion and collapsibility of soil. This study is deliberate the treatment of gypseous soil by u
... Show More