In this research, an investigation for the compatibility of the IRI-2016 and ASAPS international models was conducted to evaluate their accuracy in predicting the ionospheric critical frequency parameter (f_oF2) for the years 2009 and 2014 that represent the minimum and maximum years of solar cycle 24. The calculations of the monthly average f_oF2 values were performed for three different selected stations distributed over the mid-latitude region. These stations are Athens - Greece (23.7^o E, 37.9 ^o N), El Arenosillo - Spain (-6.78 ^o E, 37.09 ^o N), and Je Ju - South Korea (124.53 ^o E, 33.6 ^o N). The calculated v

Total Electron Content measurements derived from Athens station ionograms (ITEC),
located near Iraq, during the ascending phase of solar cycle 24 (July 2009- April 2010),
according to availability of data, are compared with the latest version of the International
Reference Ionosphere model, IRI-2012 (IRI TEC), using two options (NeQuick, IRI01-
Corr) for topside electron density.
The results obtained from both (ITEC and IRI TEC) techniques were similar, where
correlation coefficients between them are very high. Generally, the IRI predictions
overestimate the ITEC values.

The accuracy of IRI- 2012 and VOACAP models during high solar activity level have been tested to know which of them is more accurate in predicting hourly foF2 values for three Iraqi cities (Baghdad, Mosul and Basrah). The results indicated that the accuracy of them increases for all hours during Spring and Summer and decreases during Winter and Autumn especially at hours near to sunrise; i.e., both of two models have the same accuracy. And that the foF2 values predicted by VOACAP model are higher than that predicted by IRI- 2012 model for all seasons.

The aim of the research is to study the comparison between (ARIMA) Auto Regressive Integrated Moving Average and(ANNs) Artificial Neural Networks models and to select the best one for prediction the monthly relative humidity values depending upon the standard errors between estimated and observe values . It has been noted that both can be used for estimation and the best on among is (ANNs) as the values (MAE,RMSE, R2) is )0.036816,0.0466,0.91) respectively for the best formula for model (ARIMA) (6,0,2)(6,0,1) whereas the values of estimates relative to model (ANNs) for the best formula (5,5,1) is (0.0109, 0.0139 ,0.991) respectively. so that model (ANNs) is superior than (ARIMA) in a such evaluation.

Several efforts have been made to study the behavior of Total Electron Content (TEC) with many types of geomagnetic storm, the purpose of this research is to study the disturbances of the ionosphere through the TEC parameter during strong, severe and great geomagnetic storms and the validity of International Reference Ionosphere IRI model during these kinds of storms. TEC data selected for years 2000-2013 (descending solar cycle 23 to ascending cycle 24), as available from koyota Japan wdc. To find out the type of geomagnetic storms the Disturbance storm time (Dst) index was selected for the years (2000-2013) from the same website. Data from UK WDC have been taken for the solar indices sunspots number (SSN), radio flux (F10.7) and ionosp

In this research, Artificial Neural Networks (ANNs) technique was applied in an attempt to predict the water levels and some of the water quality parameters at Tigris River in Wasit Government for five different sites. These predictions are useful in the planning, management, evaluation of the water resources in the area. Spatial data along a river system or area at different locations in a catchment area usually have missing measurements, hence an accurate prediction. model to fill these missing values is essential.
The selected sites for water quality data prediction were Sewera, Numania , Kut u/s, Kut d/s, Garaf observation sites. In these five sites models were built for prediction of the water level and water quality parameters.

The influence of solar activity on the predicted ionospheric temperature parameters (electron Te, Ion Ti and neutral particle Tn) have been investigated over ionospheric Iraqi region by data generated using International Reference Ionosphere (IRI) and Madrigal models, the models result have been compared during the minimum and the maximum of solar cycle 24 for the years 2009 and 2016 respectively and for an altitudes ranged from 200-1000 km. The region under consideration spans over (latitude 29.1-37.2oN; longitude 38.9-47.7oE) within Iraq territory, the purpose of this paper is to determine the affection of the solar activity represented by the (sunspot number and solar flux) on the annual behavio

In this paper, an analytical study for the behavior of ionospheric parameters (Maximum Usable Frequency (MUF) and Optimum Traffic Frequency (FOT)) has been preformed between transmitter station (Baghdad) and many different receiver stations which are distributed randomly over Iraqi territory. The ionospheric parameters dataset has been made using ICEPAC communication model for annual time for the years 2009-2011 of the solar cycle 24. A simplified ionospheric model has been suggested which based on the correlated relationship between the geographical locations coordinates (longitudes & latitudes) of receiver stations and the dataset of the MUF and FOT parameters. The results of this study showed that the correlation between the ionos

This paper is interested in comparing the performance of the traditional methods to estimate parameter of exponential distribution (Maximum Likelihood Estimator, Uniformly Minimum Variance Unbiased Estimator) and the Bayes Estimator in the case of data to meet the requirement of exponential distribution and in the case away from the distribution due to the presence of outliers (contaminated values). Through the employment of simulation (Monte Carlo method) and the adoption of the mean square error (MSE) as criterion of statistical comparison between the performance of the three estimators for different sample sizes ranged between small, medium and large        (n=5,10,25,50,100) and different cases (wit

Abstract

The Non - Homogeneous Poisson  process is considered  as one of the statistical subjects which had an importance in other sciences and a large application in different areas as waiting raws and rectifiable systems method , computer and communication systems and the theory of reliability and many other, also it used in modeling the phenomenon that occurred by unfixed way over time (all events that changed by time).

This research deals with some of the basic concepts that are related to the Non - Homogeneous Poisson process , This research carried out two models of the Non - Homogeneous Poisson process which are the power law model , and Musa –okumto ,   to estimate th