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Rao-SVM machine learning algorithm for intrusion detection system
Published 2020“…Being that feature subset selection is considered a multi-objective optimization problem, this study proposed the Rao-SVM as an FSS mechanism; its algorithm-specific and parameter-less concept was also explored. …”
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Prediction of COVID-19 outbreak using Support Vector Machine / Muhammad Qayyum Mohd Azman
Published 2024“…A prototype architecture and a user-friendly graphical interface tailored for SVM-based outbreak predictions are developed, accompanied by detailed code snippets elucidating essential steps in data loading, encoding, scaling, and SVM model training. …”
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Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification
Published 2020“…The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…Many optimisation-based intrusion detection algorithms have been developed and are widely used for intrusion identification. …”
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AI recommendation penetration testing tool for cross-site scripting: support vector machine algorithm
Published 2025“…This research introduces a new approach to enhancing cybersecurity by integrating Support Vector Machine (SVM) algorithms with penetration testing to develop a recommendation system focused on Cross-Site Scripting (XSS) attack detection. …”
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New techniques incorporating computational intelligence based for voltage stability evaluation and improvement in power system / Nur Fadilah Ab. Aziz
Published 2014“…For comparison, another new hybrid algorithm incorporating ANN and AIS called as Artificial Immune Neural Network (AINN) for voltage stability prediction was also developed. …”
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Intelligent decision support systems: transforming smart cities management
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Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia
Published 2019“…The general objective of the study was the development of optimized hybrid debris flow models using airborne laser scanning data and Machine learning algorithms in Malaysia. …”
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Prediction of breast cancer diagnosis using machine learning in Malaysian women
Published 2024“…The three frequently used ML algorithms were deep learning, support vector machine (SVM), and cluster analysis. …”
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Enhanced ontology-based text classification algorithm for structurally organized documents
Published 2015“…This research combines the ontology and text representation for classification by developing five algorithms. The first and second algorithms namely Concept Feature Vector (CFV) and Structure Feature Vector (SFV), create feature vector to represent the document. …”
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Forensic language of property theft genre based on mathematical formulae and machine learning algorithms / Hana' Abd Razak
Published 2020“…In addition Artificial Neural Network (ANN) and Support Vector Machine (SVM) are used as classifiers. Results showed the specificity and sensitivity of SVM classifier is approximately within 50% for all tested kernels. …”
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Classification of heart disease with machine learning: a comparison of grid search, random search, and Bayesian Optimization
Published 2026“…Four commonly used machine learning algorithms: Logistic Regression (LR), Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Gradient Boosting were tested on benchmark datasets from the UC Machine Learning Repository. …”
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Performance Measurement on Deep Spiking Neural Network (DSNN) Algorithm in Flood Prediction Environment
Published 2023“…In current studies, researchers are exploring new directions by developing hybrid algorithms. …”
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A Systematic Review of Metaheuristic Algorithms in Human Activity Recognition : Applications, Trends, and Challenges
Published 2025“…These findings emphasize the potential of metaheuristic algorithms to significantly advance HAR. Future studies should explore the development of more computationally efficient hybrid models and the integration of metaheuristic optimization with deep learning architectures to enhance system robustness and adaptability.…”
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A novel approach based on machine learning and public engagement to predict water-scarcity risk in urban areas
Published 2022“…The approach was used to detect (WSR) in two ways, namely, prediction using ML models directly and using the weighted linear combination (WLC) function in GIS. Five types of ML algorithm, namely, support vector machine (SVM), multilayer perceptron, K-nearest neighbour, random forest and naïve Bayes, were incorporated for this purpose. …”
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The influence of machine learning on the predictive performance of cross-project defect prediction: empirical analysis
Published 2024“…By leveraging the rich and diverse AEEEEM dataset, this study ensures a comprehensive exploration of algorithmic influences across varied software projects. …”
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