IRAQI JOURNAL OF STATISTICAL SCIENCES

In this paper we present new conjugate gradient method for computing the minimum value of differentiable real valued function in n variables ,this method derived from Nazareth theorem , which uses the equivalence of CG and Qusi–Newton methods on quadratic function also the descent property and Conjucy conditions are proved and compared with some well know CG method showing considerable improvement .

In this study, the construction of a Fuzzy Inference Control to determine the validity of the quality of ground water wells of some of Nineveh province, through a series of observations that were obtained from the areas under study. To illustrate the importance of the model it was compared with the Discriminate Function that classify the individual to the right community. The model , has proved a model of control Fuzzy high efficiency in the determination of the validity of each well is compared to a model Discriminate Function was the only classification of the wells under study where there it is valid or invalid to drink, as well as easy construction of the computational procedures required to build a Fuzzy Inference model compared to complex computational procedures required by the Discriminate Function. The configured model can be used in future to distinguish the quality of any groundwater wells based on qualitative characteristics of the waters.
Keyword: Fuzzy Control, Discriminate Function, groundwater.

The main of this study is to give model to estimate Websites quality by Artificial Neural Network and fuzzy system to arrange these websites according to there quality depending on the values that get it during the application of the model on these webs, this models contain the most important element suggested for quality criteria like the content quality, availability, reliability, performances and some other elements that must took care when estimating websites with possibility to apply it on all webs by using numeral numbers to meager these categories, in order to get a syntactic model can depended on in estimating websites for easy access to good websites and notarization information can use it in scientific research

This paper deals with the comparison between some linear filter for time series represented by Weiner filter through autoregressive model,moving averagemodel and difference filter. An application for lung cancer Time Series in Mosul city during (1990-2000) are also considered.

This paper presents fits for neural network model , and comparative resulting forecasts with those obtained from Box-Jenkins Method. We use time series data of Tigris's monthly flow into Mosul city from 1950-1995. To perform a comparative . forecasting work through the Box-Jenkins and neural network doesn't mean working with two different or competing aspect ; on the contrary choosing a proper architecture of neural net works requires using the skills of statistical modeling . As for application , Box-Jenkins Method has given more appropriate forecasts than those given by feed forward artificial neural network . We used Minitab and SPSS programs in the statistical aspect and Alyuda program in the neural network aspect.

The past few years have witnessed great progress in scientific techniques. In addition , computer and information application have been extended to include all scientific and human fields . In this research , the mathematical model , Known as the markovian model , has been used for modeling the eternal Laa Ilaah Illa Allaah (There is no God but Allaah) after making use of the computer for forming the transition matrix and processing it. Fourthermore , some of the mathematical aspects related to this relation statement have been studied in addition to the linguistic investigation . The eguilibrium distribution of the elements of the statement has been worked out yielding a number of features of numerical mircle.
The original scientific contribution that the in this research is an other evidence that the Glorious Quraan is the eternal miracle over all ages and times.

This paper presents fits for neural network model , and comparative resulting forecasts with those obtained from Box-Jenkins Method. We use time series data of Tigris's monthly flow into Mosul city from 1950-1995. To perform a comparative . forecasting work through the Box-Jenkins and neural network doesn't mean working with two different or competing aspect ; on the contrary choosing a proper architecture of neural net works requires using the skills of statistical modeling . As for application , Box-Jenkins Method has given more appropriate forecasts than those given by feed forward artificial neural network . We used Minitab and SPSS programs in the statistical aspect and Alyuda program in the neural network aspect.

One of the Problems of image processing is that there is plenty of hidden information among the gray levels of these images. In this research the histogram technique is widely used for image enhancement to extract that information. Through the applications applied to different types of images better results were obtained compared with the original ones which were processed via the proposed algorithm.

Key Words : Digital Image Processing, Image Enhancement, Histogram, Feature Extraction.

This paper deals with the comparison between some linear filter for time series represented by Weiner filter through autoregressive model,moving averagemodel and difference filter. An application for lung cancer Time Series in Mosul city during (1990-2000) are also considered.

Factor analysis model belongs to a family of linear models and because the multivariate data sets do not vacate outliers . For this reason , this paper is concerned with Bayesian analysis of mixed normal factor analysis model . The mixture normal distribution treats the observations of a sample as they are taken from two different populations and none from single population . The model is analyzed when the common factor is (stochastic and non-stochastic) variable . We suppose that all the parameters of the model are unknown , some of them have prior distributions belong to the conjugate family.