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Semi-parametric regression function estimation for environmental pollution with measurement error using artificial flower pollination algorithm
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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).

Publication Date
Thu Aug 01 2024
Journal Name
Water Practice & Technology
Artificial neural network and response surface methodology for modeling oil content in produced water from an Iraqi oil field
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ABSTRACT<p>The majority of the environmental outputs from gas refineries are oily wastewater. This research reveals a novel combination of response surface methodology and artificial neural network to optimize and model oil content concentration in the oily wastewater. Response surface methodology based on central composite design shows a highly significant linear model with P value &lt;0.0001 and determination coefficient R2 equal to 0.747, R adjusted was 0.706, and R predicted 0.643. In addition from analysis of variance flow highly effective parameters from other and optimization results verification revealed minimum oily content with 8.5 ± 0.7 ppm when initial oil content 991 ppm, tempe</p> ... Show More
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Publication Date
Mon Feb 04 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Using Regression Analysis as Analytical Procedure to Facilitate the Decision-Making Process in The Tax Audit: An Applied Research in the General Commission of Taxes
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This research aims to clarify the advantages of using the regression method as analytical procedure in the tax audit to reducing the examination cost , time, effort, human and material resources, and represents an applied study in the General Commission of taxes. In order to achieve its objectives the research has used in the theoretical side the descriptive approach (analytical), and in the practical side regression method has been applied to the research sample represented by the soft drinks company that is subject to the tax settlement for the year 2014, where the value of sales has been verified by using the regression method without conductinga comprehensive examination. The most important results of the research indicate that the r

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
NONPARAMETRIC ESTIMATION IN DOUBLY GEOMETRIC STOCHASTIC PROCESSES
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A stochastic process {Xk, k = 1, 2, ...} is a doubly geometric stochastic process if there exists the ratio (a > 0) and the positive function (h(k) > 0), so that {α 1 h-k }; k ak X k = 1, 2, ... is a generalization of a geometric stochastic process. This process is stochastically monotone and can be used to model a point process with multiple trends. In this paper, we use nonparametric methods to investigate statistical inference for doubly geometric stochastic processes. A graphical technique for determining whether a process is in agreement with a doubly geometric stochastic process is proposed. Further, we can estimate the parameters a, b, μ and σ2 of the doubly geometric stochastic process by using the least squares estimate for Xk a

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Publication Date
Thu Dec 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
On Shrunken Estimation of Generalized Exponential Distribution
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This paper deal with the estimation of the shape parameter (a) of Generalized Exponential (GE) distribution when the scale parameter (l) is known via preliminary test single stage shrinkage estimator (SSSE) when a prior knowledge (a0) a vailable about the shape parameter as initial value due past experiences as well as suitable region (R) for testing this prior knowledge.

The Expression for the Bias, Mean squared error [MSE] and Relative Efficiency [R.Eff(×)] for the proposed estimator are derived. Numerical results about beha

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Publication Date
Wed Apr 01 2015
Journal Name
Journal Of Environmental Engineering
Using Granular Dead Anaerobic Sludge as Permeable Reactive Barrier for Remediation of Groundwater Contaminated with Phenol
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Publication Date
Sat Dec 01 2012
Journal Name
Iraqi Journal Of Physics
The transition rates for 232Th using the two component particle-hole state density with different corrections
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The particle-hole state densities have been calculated for 232Th in
the case of incident neutron with  ,  1 Z Z T T T T and   2 Z T T .
The finite well depth, surface effect, isospin and Pauli correction are
considered in the calculation of the state densities and then the
transition rates. The isospin correction function ( ) iso f has been
examined for different exciton configurations and at different
excitation energies up to 100 MeV. The present results are indicated
that the included corrections have more affected on transition rates
behavior for        , , and    above 30MeV excitation energy

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Publication Date
Tue Jun 30 2020
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
PROMOTE HUMAN RIGHTS IN CONSUMER PROTECTION AGAINST ENVIRONMENTAL, HEALTH, LEGAL, ADMINISTRATIVE AND CORRUPTION: PROMOTE HUMAN RIGHTS IN CONSUMER PROTECTION AGAINST ENVIRONMENTAL, HEALTH, LEGAL, ADMINISTRATIVE AND CORRUPTION
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Consumer protection requires seeking one official entity to accomplish its tasks. The large number of devices control and implementation in it, return to several ministries, and executive bodies lose coordination and cooperation, and unite efforts to eliminate the types of fraud and control the quality of production within the approved standards. This is in addition to the seriousness of the existence of administrative and legal corruption which hinders the role of inspection committees and representatives of official bodies with the relationship and prevents them from carrying out their duties entrusted to them or presenting them with administrative complications to thwart their duties in consumer protection. This is despite the

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Publication Date
Mon Jan 01 2018
Journal Name
International Journal Of Advanced Computer Science And Applications
Proposed an Adaptive Bitrate Algorithm based on Measuring Bandwidth and Video Buffer Occupancy for Providing Smoothly Video Streaming
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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Intelligent Systems
An efficient node selection algorithm in the context of IoT-based vehicular ad hoc network for emergency service
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Abstract<p>With the recent growth of global populations, main roads in cities have witnessed an evident increase in the number of vehicles. This has led to unprecedented challenges for authorities in managing the traffic of ambulance vehicles to provide medical services in emergency cases. Despite the high technologies associated with medical tracks and advanced traffic management systems, there is still a current delay in ambulances’ attendance in times of emergency to provide patients with vital aid. Therefore, it is indispensable to introduce a new emergency service system that enables the ambulance to reach the patient in the least congested and shortest paths. However, designing an effici</p> ... Show More
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Publication Date
Sat Jul 08 2017
Journal Name
Neural Computing And Applications
A new algorithm of modified binary particle swarm optimization based on the Gustafson-Kessel for credit risk assessment
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