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Proposition of Modified Genetic Algorithm to Estimate Additive Model by using Simulation
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Often phenomena suffer from disturbances in their data as well as the difficulty of formulation, especially with a lack of clarity in the response, or the large number of essential differences plaguing the experimental units that have been taking this data from them. Thus emerged the need to include an estimation method implicit rating of these experimental units using the method of discrimination or create blocks for each item of these experimental units in the hope of controlling their responses and make it more homogeneous. Because of the development in the field of computers and taking the principle of the integration of sciences it has been found that modern algorithms used in the field of Computer Science genetic algorithm or ant colony algorithm or bees algorithm or a swarm of birds and other originally used algorithm for the purposes of technology pertaining to distinguish between images or signals and others can be illustrated to serve the Census and check successful at it. So the choice fell on the genetic algorithm which often applied in the biology science on the subject of the analysis of DNA and genetic engineering within the modern trends of Medical Science. Proposal genetic algorithm was developed, along with C4.5 algorithm. Having been in this research integrating the work of all these algorithms mechanism Generalized Additive model to estimate some nonparametric function. Simulation was used to demonstrate the classification optimization using misclassification error and prove estimation optimization by the root mean of squares error: RMSE. The simulation has to experiment samples sizes (200, 400, 600) and (1000) replications

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Publication Date
Tue May 01 2012
Journal Name
2012 Second International Conference On Digital Information And Communication Technology And It's Applications (dictap)
The compact Genetic Algorithm for likelihood estimator of first order moving average model
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Recently Genetic Algorithms (GAs) have frequently been used for optimizing the solution of estimation problems. One of the main advantages of using these techniques is that they require no knowledge or gradient information about the response surface. The poor behavior of genetic algorithms in some problems, sometimes attributed to design operators, has led to the development of other types of algorithms. One such class of these algorithms is compact Genetic Algorithm (cGA), it dramatically reduces the number of bits reqyuired to store the poulation and has a faster convergence speed. In this paper compact Genetic Algorithm is used to optimize the maximum likelihood estimator of the first order moving avergae model MA(1). Simulation results

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Publication Date
Sun Mar 01 2020
Journal Name
Baghdad Science Journal
Eyewitnesses’ Visual Recollection in Suspect Identification by using Facial Appearance Model
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Facial recognition has been an active field of imaging science. With the recent progresses in computer vision development, it is extensively applied in various areas, especially in law enforcement and security. Human face is a viable biometric that could be effectively used in both identification and verification. Thus far, regardless of a facial model and relevant metrics employed, its main shortcoming is that it requires a facial image, against which comparison is made. Therefore, closed circuit televisions and a facial database are always needed in an operational system. For the last few decades, unfortunately, we have experienced an emergence of asymmetric warfare, where acts of terrorism are often committed in secluded area with no

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Publication Date
Mon Aug 05 2019
Journal Name
Gen. Lett. Math
Building a three-dimensional maritime transport model to find the best solution by using the heuristic algorithm
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The aim of this research is to construct a three-dimensional maritime transport model to transport nonhomogeneous goods (k) and different transport modes (v) from their sources (i) to their destinations (j), while limiting the optimum quantities v ijk x to be transported at the lowest possible cost v ijk c and time v ijk t using the heuristic algorithm, Transport problems have been widely studied in computer science and process research and are one of the main problems of transport problems that are usually used to reduce the cost or times of transport of goods with a number of sources and a number of destinations and by means of transport to meet the conditions of supply and demand. Transport models are a key tool in logistics an

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Publication Date
Thu Aug 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Analyzing current and future direction of non-oil primary balance: Case Study of Iraq Using Exponential Smoothing model
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In recent years, non-oil primary balance indicator has been given considerable financial important in rentier state. It highly depends on this indicator to afford a clear and proper picture of public finance situation in term of appropriate and sustainability in these countries, due to it excludes the effect of oil- rental from compound of financial accounts which provide sufficient information to economic policy makers of how economy is able to create potential added value and then changes by eliminating one sided shades of economy. In Iraq, since, 2004, the deficit in value of this indicator has increased, due to almost complete dependence on the revenues of the oil to finance the budget and the obvious decline of the non-oil s

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Publication Date
Sat Oct 02 2021
Journal Name
International Journal Of Nonlinear Analysis And Applications
Using the wavelet analysis to estimate the nonparametric regression model in the presence of associated errors
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Abstract The wavelet shrink estimator is an attractive technique when estimating the nonparametric regression functions, but it is very sensitive in the case of a correlation in errors. In this research, a polynomial model of low degree was used for the purpose of addressing the boundary problem in the wavelet reduction in addition to using flexible threshold values in the case of Correlation in errors as it deals with those transactions at each level separately, unlike the comprehensive threshold values that deal with all levels simultaneously, as (Visushrink) methods, (False Discovery Rate) method, (Improvement Thresholding) and (Sureshrink method), as the study was conducted on real monthly data represented in the rates of theft crimes f

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Publication Date
Tue Nov 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Proposal of Using Principle of Maximizing Entropy of Generalized Gamma Distribution to Estimate the Survival probabilities of the Population in Iraq
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In this research we been estimated the survival function for data suffer from the disturbances and confusion of Iraq Household Socio-Economic Survey: IHSES II 2012 , to data from a five-year age groups follow the distribution of the Generalized Gamma: GG. It had been used two methods for the purposes of estimating and fitting which is the way the Principle of Maximizing Entropy: POME, and method of booting to nonparametric smoothing function for Kernel, to overcome the mathematical problems plaguing integrals contained in this distribution in particular of the integration of the incomplete gamma function, along with the use of traditional way in which is the Maximum Likelihood: ML. Where the comparison on the basis of the method of the Cen

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Publication Date
Tue Oct 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Scheduling projects using dynamic programming style and smart algorithm
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The aim of this research is to compare traditional and modern methods to obtain the optimal solution using dynamic programming and intelligent algorithms to solve the problems of project management.

It shows the possible ways in which these problems can be addressed, drawing on a schedule of interrelated and sequential activities And clarifies the relationships between the activities to determine the beginning and end of each activity and determine the duration and cost of the total project and estimate the times used by each activity and determine the objectives sought by the project through planning, implementation and monitoring to maintain the budget assessed 

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Publication Date
Sun May 01 2022
Journal Name
Journal Of Engineering
Attitude and Altitude Control of Quadrotor Carrying a Suspended Payload using Genetic Algorithm
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The need for quick airborne transportation is critical, especially in emergencies. Drones with suspended payloads might be used to accomplish quick airborne transportation. Due to the environment or the drone's motion, the slung load may oscillate and lead the drone to fall. The altitude and attitude controls are the backbones of the drone's stability, and they must be adequately designed. Because of their symmetrical and simple structure, quadrotor helicopters are one of the most popular drone classes. In this work, a genetic algorithm with two weighted terms fitness function is used to adjust a Proportional-Integral-Derivative (PID) controller to compensate for the altitude and attitude controllers in a quadrotor drone with a slun

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Publication Date
Sun May 01 2022
Journal Name
Journal Of Engineering
Attitude and Altitude Control of Quadrotor Carrying a Suspended Payload using Genetic Algorithm
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The need for quick airborne transportation is critical, especially in emergencies. Drones with suspended payloads might be used to accomplish quick airborne transportation. Due to the environment or the drone's motion, the slung load may oscillate and lead the drone to fall. The altitude and attitude controls are the backbones of the drone's stability, and they must be adequately designed. Because of their symmetrical and simple structure, quadrotor helicopters are one of the most popular drone classes. In this work, a genetic algorithm with two weighted terms fitness function is used to adjust a Proportional-Integral-Derivative (PID) controller to compensate for the altitude and attitude controllers in a quadrotor drone

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Publication Date
Fri Dec 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Multi – Linear in Multiple Nonparametric Regression , Detection and Treatment Using Simulation
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             It is the regression analysis is the foundation stone of knowledge of statistics , which mostly depends on the ordinary least square method , but as is well known that the way the above mentioned her several conditions to operate accurately and the results can be unreliable , add to that the lack of certain conditions make it impossible to complete the work and analysis method and among those conditions are the multi-co linearity problem , and we are in the process of detected that problem between the independent variables using farrar –glauber test , in addition to the requirement linearity data and the lack of the condition last has been resorting to the

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