This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spent to achieve the best classification accuracy.
ABSTRACT: In this research SnO2 thin films have been prepared by using hot plate atmospheric pressure chemical vapor deposition (HPCVD) on glass and Si (n-type) substrates at various temperatures. Optical properties have been measured by UV-VIS spectrophotometer, maximum transmittance about (94%) at 400 0C. Structure properties have been studied by using X-ray diffraction (XRD) , its shows that all films have a crystalline structure in nature and by increasing growth temperature from(350-500) 0C diffraction peaks becomes sharper and grain size has been change. Atomic force microscopy (AFM) uses to analyze the morphology of the Tine Oxides surface structure. Roughness & Root mean square for different temperature have been investigated. The r
... Show MoreThe objective of the study is to demonstrate the predictive ability is better between the logistic regression model and Linear Discriminant function using the original data first and then the Home vehicles to reduce the dimensions of the variables for data and socio-economic survey of the family to the province of Baghdad in 2012 and included a sample of 615 observation with 13 variable, 12 of them is an explanatory variable and the depended variable is number of workers and the unemployed.
Was conducted to compare the two methods above and it became clear by comparing the logistic regression model best of a Linear Discriminant function written
... Show MorePrediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay
... Show MoreFrequent data in weather records is essential for forecasting, numerical model development, and research, but data recording interruptions may occur for various reasons. So, this study aims to find a way to treat these missing data and know their accuracy by comparing them with the original data values. The mean method was used to treat daily and monthly missing temperature data. The results show that treating the monthly temperature data for the stations (Baghdad, Hilla, Basra, Nasiriya, and Samawa) in Iraq for all periods (1980-2020), the percentage for matching between the original and the treating values did not exceed (80%). So, the period was divided into four periods. It was noted that most of the congruence values increased, re
... Show MoreGravity and magnetic data are used to study the tectonic situation of Al-Kut- Al-
Hai and surrounding areas in central Iraq. The study included application of many
processing and interpretation programs. The window method with different spacing
was used to separate the residual from regional anomalies for gravity and magnetic
data. The Total Horizontal Derivative (THDR) techniques used to identify the fault
trends in the basement and sedimentary cover rocks depending upon gravity and
magnetic data. The identified faults in the study area show (NW-SE), (NE-SW) (NS)
and (E-W) trends. It is believed that these faults extending from the basement to
the upper most layer of the sedimentary cover rocks.
Big data usually running in large-scale and centralized key management systems. However, the centralized key management systems are increasing the problems such as single point of failure, exchanging a secret key over insecure channels, third-party query, and key escrow problem. To avoid these problems, we propose an improved certificate-based encryption scheme that ensures data confidentiality by combining symmetric and asymmetric cryptography schemes. The combination can be implemented by using the Advanced Encryption Standard (AES) and Elliptic Curve Diffie-Hellman (ECDH). The proposed scheme is an enhanced version of the Certificate-Based Encryption (CBE) scheme and preserves all its advantages. However
... Show MoreThe current research discussed biophysics data as a theoretical and applied knowledge base linking industrial design with the natural sciences at the level of applied strategies through which we can enrich the knowledge base of industrial design. The research focused on two main aspects of the scientific references for biophysics, namely: electromagnetism, and biomechanics. According to the performance and functional applications in designing the functions of industrial products at the electromagnetic level, it was found that remote sensing applications: such as fire sensors that were adopted from the insect (Black Beetle) and that their metaphors enable them to hear fire, and collision sensors, which were adopted from the insect
... Show MoreIn this paper, ARIMA model was used for Estimating the missing data(air temperature, relative humidity, wind speed) for mean monthly variables in different time series at three stations (Sinjar, Baghdad , AL.Hai) which represented different parts of Iraq from north to south respectively
This research includes structure interpretation of the Yamama Formation (Lower Cretaceous) and the Naokelekan Formation (Jurassic) using 2D seismic reflection data of the Tuba oil field region, Basrah, southern Iraq. The two reflectors (Yamama and Naokelekan) were defined and picked as peak and tough depending on the 2D seismic reflection interpretation process, based on the synthetic seismogram and well log data. In order to obtain structural settings, these horizons were followed over all the regions. Two-way travel-time maps, depth maps, and velocity maps have been produced for top Yamama and top Naokelekan formations. The study concluded that certain longitudinal enclosures reflect anticlines in the east and west of the study ar
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