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Non-linear support vector machine classification models using kernel tricks with applications
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The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample sizes (50, 100, 200). A comparison between non-linear SVM and two standard classification methods was illustrated using various compared features. Our study has shown that the non-linear SVM method gives better results by checking: sensitivity, specificity, accuracy, and time-consuming. © 2024 Author(s).

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Publication Date
Sat Jun 06 2020
Journal Name
Journal Of The College Of Education For Women
Spatial Analysis of Soil Characteristics and its Effect on Determining the Susceptibility of lands of the RasheedRegion: A Study in Soil Geography
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Twelve pends were selected and distributed on three verticals transects paths on the Tigers river in Al Rasheed county.Passing through land covers, that classified and covers the whole region. Based on the 8 Landsat of the year 2015. It was oriental classified by using Erdas 10.2 . The pedons were distributed on the area of each varicty of these classes. the series of soil according of the transect series (DW74,MMg,DMu6 , Df96) respectively were represented P1 , P2 , P3 , P4  .

The second transits series(DM97,MM5,DM96,DF115) respectively were  represented P5 , P6 , P7 , P8  .The third  transits series(DM46,MMg,MF12,MM11) re

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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
DESIGN OF A VARIABLE GAIN NONLINEAR FUZZY CONTROLLER AND PERFORMANCE ENHANCEMENT DUE TO GAIN VARIATION
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In this paper, variable gain nonlinear PD and PI fuzzy logic controllers are designed and the effect of the variable gain characteristic of these controllers is analyzed to show its contribution in enhancing the performance of the closed loop system over a conventional linear PID controller. Simulation results and time domain performance characteristics show how these fuzzy controllers outperform the conventional PID controller when used to control a nonlinear plant and a plant that has time delay.

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Publication Date
Tue Mar 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
The Bayesian Estimation for The Shape Parameter of The Power Function Distribution (PFD-I) to Use Hyper Prior Functions
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The objective of this study is to examine the properties of Bayes estimators of the shape parameter of the Power Function Distribution (PFD-I), by using two different prior distributions for the parameter θ and different loss functions that were compared with the maximum likelihood estimators. In many practical applications, we may have two different prior information about the prior distribution for the shape parameter of the Power Function Distribution, which influences the parameter estimation. So, we used two different kinds of conjugate priors of shape parameter θ of the <

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Publication Date
Mon Feb 01 2021
Journal Name
Journal Of Engineering
Electrical Conductivity as a General Predictor of Multiple Parameters in Tigris River Based on Statistical Regression Model
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Surface water samples from different locations within Tigris River's boundaries in Baghdad city have been analyzed for drinking purposes. Correlation coefficients among different parameters were determined. An attempt has been made to develop linear regression equations to predict the concentration of water quality constituents having significant correlation coefficients with electrical conductivity (EC). This study aims to find five regression models produced and validated using electrical conductivity as a predictor to predict total hardness (TH), calcium (Ca), chloride (Cl), sulfate (SO4), and total dissolved solids (TDS). The five models showed good/excellent prediction ability of the parameters mentioned

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Publication Date
Wed Jun 01 2022
Journal Name
Iraqi Journal Of Physics
Statistical Analysis and Forecasting of Rainfall Patterns and Trends in Gombe North-Eastern Nigeria
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Rainfall in Nigeria is highly dynamic and variable on a temporal and spatial scale. This has taken a more pronounced dimension due to climate change. In this study, Standard Precipitation Index (SPI) and Mann-Kendall test statistical tools were employed to analyze rainfall trends and patterns in Gombe metropolis between 1990 and 2020 and the ARIMA model was used for making the forecast for ten (10) years. Daily rainfall data of 31 years obtained from Nigerian Meteorological Agency, (NIMET) was used for the study. The daily rainfall data was subjected to several analyses. Standard precipitation index showed that alternation of wet and dry period conditions had been witnessed in the study area. The result obtained showed that there is an u

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Publication Date
Mon Jan 01 2024
Journal Name
Lecture Notes In Networks And Systems
Proceedings of Ninth International Congress on Information and Communication Technology
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The investigation of signature validation is crucial to the field of personal authenticity. The biometrics-based system has been developed to support some information security features.Aperson’s signature, an essential biometric trait of a human being, can be used to verify their identification. In this study, a mechanism for automatically verifying signatures has been suggested. The offline properties of handwritten signatures are highlighted in this study which aims to verify the authenticity of handwritten signatures whether they are real or forged using computer-based machine learning techniques. The main goal of developing such systems is to verify people through the validity of their signatures. In this research, images of a group o

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Publication Date
Sat Aug 03 2024
Journal Name
Proceedings Of Ninth International Congress On Information And Communication Technology
Offline Signature Verification Based on Neural Network
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The investigation of signature validation is crucial to the field of personal authenticity. The biometrics-based system has been developed to support some information security features.Aperson’s signature, an essential biometric trait of a human being, can be used to verify their identification. In this study, a mechanism for automatically verifying signatures has been suggested. The offline properties of handwritten signatures are highlighted in this study which aims to verify the authenticity of handwritten signatures whether they are real or forged using computer-based machine learning techniques. The main goal of developing such systems is to verify people through the validity of their signatures. In this research, images of a group o

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Publication Date
Fri Jan 01 2016
Journal Name
Journal Of Engineering
Semantic Similarity Assessment of Volunteered Geographic Information
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The recent development in communication technologies between individuals allows for the establishment of more informal collaborative map data projects which are called volunteered geographic information (VGI). These projects, such as OpenStreetMap (OSM) project, seek to create free alternative maps which let users add or input new materials to the data of others. The information of different VGI data sources is often not compliant to any standard and each organization is producing a dataset at various level of richness. In this research the assessment of semantic data quality provided by web sources, e.g. OSM will depend on a comparison with the information from standard sources. This will include the validity of semanti

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Publication Date
Wed Dec 18 2019
Journal Name
Baghdad Science Journal
Modeling Human Capital Impact on the Development of the Iraqi Oil Industry
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Iraq has the second largest proven oil reserves in the world. According to oil experts, it is expected that the Iraq's reserves to rise to 200+ billion barrels of high-grade crude.

Oil is a strategic commodity for producing and exporting countries in general, and Iraq in particular, as demonstrated by the international experience that oil is an important means to achieve economic growth, an important tool in the overall economic, social and political development. It is also an important source of hard currency for any national economy and a means to connect the local economy and the global economy. In this paper we focus our attention on selecting the best regression model that explain the effect of human capita

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Publication Date
Sat Jan 02 2021
Journal Name
The International Journal Of Nonlinear Analysis And Application
Atan regularized for the high dimensional Poisson regression model
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Variable selection in Poisson regression with high dimensional data has been widely used in recent years. we proposed in this paper using a penalty function that depends on a function named a penalty. An Atan estimator was compared with Lasso and adaptive lasso. A simulation and application show that an Atan estimator has the advantage in the estimation of coefficient and variables selection.

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