Preferred Language
Articles
/
qWHWdZkBdMdGkNqjyCeP
Non-linear support vector machine classification models using kernel tricks with applications
...Show More Authors

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).

Scopus Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Fri Feb 28 2025
Journal Name
Energies
Synergizing Machine Learning and Physical Models for Enhanced Gas Production Forecasting: A Comparative Study of Short- and Long-Term Feasibility
...Show More Authors

Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m

... Show More
View Publication Preview PDF
Crossref (1)
Scopus Clarivate Crossref
Publication Date
Mon May 01 2017
Journal Name
Energy Procedia
A Coupled Model of the Linear Joule Engine with Embedded Tubular Permanent Magnet Linear Alternator
...Show More Authors

Scopus (16)
Crossref (12)
Scopus Clarivate Crossref
Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Computer, Communication, Control And System Engineering
A Framework for Predicting Airfare Prices Using Machine Learning
...Show More Authors

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci

... Show More
View Publication
Crossref (4)
Crossref
Publication Date
Thu Sep 01 2022
Journal Name
Iraqi Journal Of Computers, Communications, Control And Systems Engineering
A Framework for Predicting Airfare Prices Using Machine Learning
...Show More Authors

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre

... Show More
View Publication Preview PDF
Publication Date
Fri Jan 01 2016
Journal Name
Middle-east Journal Of Scientific Research
Question Classification Using Different Approach: A Whole Review
...Show More Authors

Preview PDF
Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Engineering
A Fuzzy Logic Controller Based Vector Control of IPMSM Drives
...Show More Authors

This paper explores a fuzzy-logic based speed controller of an interior permanent magnet synchronous motor (IPMSM) drive based on vector control. PI controllers were mostly used in a speed control loop based field oriented control of an IPMSM. The fundamentals of fuzzy logic algorithms as related to drive control applications are illustrated. A complete comparison between two tuning algorithms of the classical PI controller and the fuzzy PI controller is explained. A simplified fuzzy logic controller (FLC) for the IPMSM drive has been found to maintain high performance standards with a much simpler and less computation implementation. The Matlab simulink results have been given for different mechanical operating conditions. The simulated

... Show More
View Publication Preview PDF
Crossref
Publication Date
Thu Oct 01 2020
Journal Name
Test Engineering & Management
Strengthening of non-liner finite element RCMD Beam with Large Square Opening Using CFRP
...Show More Authors

Publication Date
Sun Nov 01 2009
Journal Name
Tencon 2009 - 2009 Ieee Region 10 Conference
Optimizing the MPLS support for real time IPv6-Flows using MPLS-PHS approach
...Show More Authors

View Publication
Scopus (4)
Scopus Crossref
Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Solid Waste Treatment Using Multi-Criteria Decision Support Methods Case Study Lattakia City
...Show More Authors

Lattakia city faces many problems related to the mismanagement of solid waste, as the disposal process is limited to the random Al-Bassa landfill without treatment. Therefore, solid waste management poses a special challenge to decision-makers by choosing the appropriate tool that supports strategic decisions in choosing municipal solid waste treatment methods and evaluating their management systems. As the human is primarily responsible for the formation of waste, this study aims to measure the degree of environmental awareness in the Lattakia Governorate from the point of view of the research sample members and to discuss the effect of the studied variables (place of residence, educational level, gender, age, and professional status) o

... Show More
View Publication Preview PDF
Scopus (5)
Scopus Crossref
Publication Date
Mon Mar 29 2021
Journal Name
Journal Of Engineering
Numerical Simulation of Water Distribution with Uptake Root in Drip Irrigation using Different Soil Hydraulic Models
...Show More Authors

Surface drip irrigation is one of the most conservative irrigation techniques that help control providing water directly on the soil through the emitters. It can supply fertilizer and providing water directly to plant roots by drippers. One of the essential needs for trickle irrigation nowadays is to obtain more knowledge about the moisture pattern under the trickling source for various types of soil with various discharge levels with trickle irrigation. Simulation numerical using HYDRUS-2D software, version 2.04 was used to estimate an equation for the wetted area from a single surface drip irrigation in unsaturated soil is taking into account water uptake by roots. In this paper, using two soil types were used, namely

... Show More
View Publication Preview PDF
Crossref