The grey system model GM(1,1) is the model of the prediction of the time series and the basis of the grey theory. This research presents the methods for estimating parameters of the grey model GM(1,1) is the accumulative method (ACC), the exponential method (EXP), modified exponential method (Mod EXP) and the Particle Swarm Optimization method (PSO). These methods were compared based on the Mean square error (MSE) and the Mean Absolute percentage error (MAPE) as a basis comparator and the simulation method was adopted for the best of the four methods, The best method was obtained and then applied to real data. This data represents the consumption rate of two types of oils a heavy fuel (HFO) and diesel fuel (D.O) and the use of tests to confirm the accuracy of the grey model. After obtaining the results, the best method to estimate the parameters of the grey model GM(1,1) is the method of the Particle Swarm Optimization method (PSO) It has been used to treatment the missing values in the data and in the prediction where it has been shown to have the best results
The goal of current research is to identify the difficulties in the application of modern physics in the middle schools of the province of Baghdad schools from the perspective of teachers of physics trends, sample search of (127) teachers, Karkh Third Directorate, and use Researcher questionnaire data collection tool after applying it to teachers who have experience (5) years and more after confirmation of the validity and reliability of the scale (the tool) researcher has used the averages for the purpose of interpreting the results. the results showed that the difficulties have been in the order following: (difficulties related educational environment of modern trends of teaching, curriculum-related difficulties, difficulties rel
... Show MoreIn this research we study a variance component model, Which is the one of the most important models widely used in the analysis of the data, this model is one type of a multilevel models, and it is considered as linear models , there are three types of linear variance component models ,Fixed effect of linear variance component model, Random effect of linear variance component model and Mixed effect of linear variance component model . In this paper we will examine the model of mixed effect of linear variance component model with one –way random effect ,and the mixed model is a mixture of fixed effect and random effect in the same model, where it contains the parameter (μ) and treatment effect (τi ) which has
... Show MoreIn this paper , two method which deal with finding the optimal value for adaptive smoothing constant, are compared .This constant is used in adaptive Single Exponential Smoothing (ASES).
The comparing is between a method uses time domain and another uses frequency domain when the data contain outlier value for autoregressive model of order one AR(1) , or Markov Model, when the time series are stationary and non stationary with deferent samples .
Journal of Studies and Researches of Sport Education
Nonlinear time series analysis is one of the most complex problems ; especially the nonlinear autoregressive with exogenous variable (NARX) .Then ; the problem of model identification and the correct orders determination considered the most important problem in the analysis of time series . In this paper , we proposed splines estimation method for model identification , then we used three criterions for the correct orders determination. Where ; proposed method used to estimate the additive splines for model identification , And the rank determination depends on the additive property to avoid the problem of curse dimensionally . The proposed method is one of the nonparametric methods , and the simulation results give a
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بفضل التقدم الذي حصل في الحاسبات في العقد الأخير والذي انعكست آثاره على البرامج الجاهزة اعتبرت المشكلة التي في حدود بضعة آلاف من المتغيرات والقيود من المشاكل الصغيرة إذ تم حل مشاكل بعشرات الآلاف أو مئات الآلاف من المتغيرات المستمرة حلا مناسبا.وبفضل التقدم التكنولوجي للحاسبات وسرعة معاملتها للبيانات والمعادلات تم بناء برامج جاهزة لأساليب بحوث العمليات ومعالجة المشاكل الإدار
... Show MoreIn this study, we made a comparison between LASSO & SCAD methods, which are two special methods for dealing with models in partial quantile regression. (Nadaraya & Watson Kernel) was used to estimate the non-parametric part ;in addition, the rule of thumb method was used to estimate the smoothing bandwidth (h). Penalty methods proved to be efficient in estimating the regression coefficients, but the SCAD method according to the mean squared error criterion (MSE) was the best after estimating the missing data using the mean imputation method
This paper includes the application of Queuing theory with of Particle swarm algorithm or is called (Intelligence swarm) to solve the problem of The queues and developed for General commission for taxes /branch Karkh center in the service stage of the Department of calculators composed of six employees , and it was chosen queuing model is a single-service channel M / M / 1 according to the nature of the circuit work mentioned above and it will be divided according to the letters system for each employee, and it was composed of data collection times (arrival time , service time, departure time)
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In this research was the study of a single method of estimation and testing parameters mediating variables (Mediation) in a specimen structural equations SEM a bootstrap method, for the purpose of application of the integrated survey of the situation Marital data and health mirror Iraqi (I-WISH) for the year 2011 from the Ministry of Planning - device Central Bureau of Statistics, and applied to the appropriate data from the terms of the data to a form of structural equation SEM using factor analysis affirmative (Confirmatory Factor analysis) CFA As a way to see the match variables that make up the model, and after confirming the model matching or suitability are having the effect of variables mediation in the model tested by the
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