Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing flower pollination algorithm in the environmental field to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement. We estimate the regression function of the semi-parametric model by estimating the parametric model and estimating the non-parametric model, the parametric model is estimated by using an instrumental variables method (Wald method, Bartlett’s method, and Durbin’s method), The nonparametric model is estimated by using kernel smoothing (Nadaraya Watson), K-Nearest Neighbor smoothing and Median smoothing. The Flower Pollination algorithms were employed and structured in building the ecological model and estimating the semi-parametric regression function with measurement errors in the explanatory and dependent variables, then compare the models to choose the best model used in the environmental scope measurement errors, where the comparison between the models is done using the mean square error (MSE).
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In this research, a variable stiffness actuator is proposed to enhance the damping of the mechanical vibrating system. The frequency response analysis of the vibrating system is dependant in order to analyze and synthesis this semi-active damping, where the suggested process is using active filter to estimate the present frequency of the vibration system, and this will limit the value of the stiffness of the vibrated system. Two active filter s are needed, low-pass-filter (LPF) to choose the higher stiffness of the actuator at small frequencies as well as more damping and high-pass-filter (HPF) to choose the lower stiffness of the actuator at high frequencies as well as more damping, and so
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In this research we discussed the parameter estimation and variable selection in Tobit quantile regression model in present of multicollinearity problem. We used elastic net technique as an important technique for dealing with both multicollinearity and variable selection. Depending on the data we proposed Bayesian Tobit hierarchical model with four level prior distributions . We assumed both tuning parameter are random variable and estimated them with the other unknown parameter in the model .Simulation study was used for explain the efficiency of the proposed method and then we compared our approach with (Alhamzwi 2014 & standard QR) .The result illustrated that our approach
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Throughout this paper R represents commutative ring with identity, and M is a unitary left R-module. The purpose of this paper is to study a new concept, (up to our knowledge), named a semi-extending modules, as generalization of extending modules, where an Rmodule M is called semi-extending if every sub module of M is a semi-essential in a direct summand of M. Various properties of semi-extending module are considered. Moreover, we investigate the relationships between semi-extending modules and other related concepts, such as CLS-modules and FI- extending modules.
Let be a commutative ring with 1 and be a left unitary . In this paper, the generalizations for the notions of compressible module and retractable module are given.
An is termed to be semi-essentially compressible if can be embedded in every of a non-zero semi-essential submodules. An is termed a semi-essentially retractable module, if for every non-zero semi-essentially submodule of an . Some of their advantages characterizations and examples are given. We also study the relation between these classes and some other classes of modules.
Let be a commutative ring with 1 and be left unitary . In this paper we introduced and studied concept of semi-small compressible module (a is said to be semi-small compressible module if can be embedded in every nonzero semi-small submodule of . Equivalently, is semi-small compressible module if there exists a monomorphism , , is said to be semi-small retractable module if , for every non-zero semi-small sub module in . Equivalently, is semi-small retractable if there exists a homomorphism whenever . In this paper we introduce and study the concept of semi-small compressible and semi-small retractable s as a generalization of compressible and retractable respectively and give some of their adv
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Let be an associative ring with identity and let be a unitary left -module. Let be a non-zero submodule of .We say that is a semi- - hollow module if for every submodule of such that is a semi- - small submodule ( ). In addition, we say that is a semi- - lifting module if for every submodule of , there exists a direct summand of and such that
The main purpose of this work was to develop the properties of these classes of module.
Let be a commutative ring with 1 and be left unitary . In this paper we introduced and studied concept of semi-small compressible module (a is said to be semi-small compressible module if can be embedded in every nonzero semi-small submodule of . Equivalently, is semi-small compressible module if there exists a monomorphism , , is said to be semi-small retractable module if , for every non-zero semi-small sub module in . Equivalently, is semi-small retractable if there exists a homomorphism whenever .
In this paper we introduce and study the concept of semi-small compressible and semi-small retractable s as a generalization of compressible and retractable respectively and give some of
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