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Multilayer Perceptron for analyzing satellite data
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Different ANN architectures of MLP have been trained by BP and used to analyze Landsat TM images. Two different approaches have been applied for training: an ordinary approach (for one hidden layer M-H1-L & two hidden layers M-H1-H2-L) and one-against-all strategy (for one hidden layer (M-H1-1)xL, & two hidden layers (M-H1-H2-1)xL). Classification accuracy up to 90% has been achieved using one-against-all strategy with two hidden layers architecture. The performance of one-against-all approach is slightly better than the ordinary approach

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Publication Date
Mon Oct 01 2018
Journal Name
Iraqi Journal Of Physics
Classification of brain tumors using the multilayer perceptron artificial neural network
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Information from 54 Magnetic Resonance Imaging (MRI) brain tumor images (27 benign and 27 malignant) were collected and subjected to multilayer perceptron artificial neural network available on the well know software of IBM SPSS 17 (Statistical Package for the Social Sciences). After many attempts, automatic architecture was decided to be adopted in this research work. Thirteen shape and statistical characteristics of images were considered. The neural network revealed an 89.1 % of correct classification for the training sample and 100 % of correct classification for the test sample. The normalized importance of the considered characteristics showed that kurtosis accounted for 100 % which means that this variable has a substantial effect

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Publication Date
Tue Apr 02 2019
Journal Name
Artificial Intelligence Research
A three-stage learning algorithm for deep multilayer perceptron with effective weight initialisation based on sparse auto-encoder
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A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

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Publication Date
Sat Oct 30 2021
Journal Name
Iraqi Journal Of Science
An Application of Data Mining Algorithms for Analyzing Psychological Researches
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     Computer science has evolved to become the basis for evolution and entered into all areas of life where the use of computer has been developed in all scientific, military, commercial and health institutions. In addition, it has been applied in residential and industrial projects due to the high capacity and ability to achieve goals in a shorter time and less effort. In this research, the computer, its branches, and algorithms will be invested in the psychological field. In general, in psychological fields, a questionnaire model is created according to the requirements of the research topic. The model contains many questions that are answered by the individuals of the sample space chosen by the researcher. Often,

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Publication Date
Sun Sep 04 2011
Journal Name
Baghdad Science Journal
Study of contrast between satellite image data and ground data
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Spot panchromatic satellite image had been employed to study and know the difference Between ground and satellite data( DN ,its values varies from 0-255) where it is necessary to convert these DN values to absolute radiance values through special equations ,later it converted to spectral reflectance values .In this study a monitoring of the environmental effect resulted from throwing the sewage drainages pollutants (industrial and home) into the Tigris river water in Mosul, was achieved, which have an effect mostly on physical characters specially color and turbidity which lead to the variation in Spectral Reflectance of the river water ,and it could be detected by using many remote sensing techniques. The contaminated areas within th

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Publication Date
Tue Aug 15 2023
Journal Name
Journal Of Economics And Administrative Sciences
Machine Learning Techniques for Analyzing Survival Data of Breast Cancer Patients in Baghdad
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The Machine learning methods, which are one of the most important branches of promising artificial intelligence, have great importance in all sciences such as engineering, medical, and also recently involved widely in statistical sciences and its various branches, including analysis of survival, as it can be considered a new branch used to estimate the survival and was parallel with parametric, nonparametric and semi-parametric methods that are widely used to estimate survival in statistical research. In this paper, the estimate of survival based on medical images of patients with breast cancer who receive their treatment in Iraqi hospitals was discussed. Three algorithms for feature extraction were explained: The first principal compone

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Publication Date
Sat Jun 29 2013
Journal Name
Journal Of Statistics Applications & Probability
Analyzing Skewed Data with the Epsilon Skew Gamma distribution
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A new distribution, the Epsilon Skew Gamma (ESΓ ) distribution, which was first introduced by Abdulah [1], is used on a near Gamma data. We first redefine the ESΓ distribution, its properties, and characteristics, and then we estimate its parameters using the maximum likelihood and moment estimators. We finally use these estimators to fit the data with the ESΓ distribution

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Publication Date
Tue Jun 13 2023
Journal Name
Journal Of Survey In Fisheries Sciences
Spectrum Analyzing X-ray Data Image (FITS) Using Ds9 Program
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n this study, data or X-ray images Fixable Image Transport System (FITS) of objects were analyzed, where energy was collected from the body by several sensors; each sensor receives energy within a specific range, and when energy was collected from all sensors, the image was formed carrying information about that body. The images can be transferred and stored easily. The images were analyzed using the DS9 program to obtain a spectrum for each object,an energy corresponding to the photons collected per second. This study analyzed images for two types of objects (globular and open clusters). The results showed that the five open star clusters contain roughly t

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Publication Date
Tue May 20 2008
Journal Name
Journal Of Planner And Development
Estimating Water Quality from Satellite Image and Reflectance Data
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The useful of remote sensing techniques in Environmental Engineering and another science is to save time, Coast and efforts, also to collect more accurate information under monitoring mechanism. In this research a number of statistical models were used for determining the best relationships between each water quality parameter and the mean reflectance values generated for different channels of radiometer operate simulated to the thematic Mappar satellite image. Among these models are the regression models which enable us to as certain and utilize a relation between a variable of interest. Called a dependent variable; and one or more independent variables

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Publication Date
Tue Aug 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Modis Satellite Data Evaluation for Detecting the Dust Storm Using Remote Sensing Techniques Over Iraq
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Abstract<p>The phenomena of Dust storm take place in barren and dry regions all over the world. It may cause by intense ground winds which excite the dust and sand from soft, arid land surfaces resulting it to rise up in the air. These phenomena may cause harmful influences upon health, climate, infrastructure, and transportation. GIS and remote sensing have played a key role in studying dust detection. This study was conducted in Iraq with the objective of validating dust detection. These techniques have been used to derive dust indices using Normalized Difference Dust Index (NDDI) and Middle East Dust Index (MEDI), which are based on images from MODIS and in-situ observation based on hourly wi</p> ... Show More
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Publication Date
Sun Jan 01 2023
Journal Name
Petroleum And Coal
Analyzing of Production Data Using Combination of empirical Methods and Advanced Analytical Techniques
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