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Prioritisation Assessment and Robust Predictive System for Medical Equipment: A Comprehensive Strategic Maintenance Management
Published 2024journal::journal article -
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A machine learning approach of predicting high potential archers by means of physical fitness indicators
Published 2019“…k-nearest neighbour (k-NN) has been shown to be an effective learning algorithm for classification and prediction. …”
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Cooperative spectrum sensing based on machine learning in cognitive radio vehicular network / Mohammad Asif Hossain
Published 2022“…In this thesis, local sensing results are produced by SUs or vehicles by selecting the best spectrum sensing technique. The selection would be made based on the hybrid machine learning (ML) algorithm. …”
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4
A machine learning approach of predicting high potential archers by means of physical fitness indicators
Published 2019“…k-nearest neighbour (k-NN) has been shown to be an effective learning algorithm for classification and prediction. …”
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5
Trap colour strongly affects the ability of deep learning models to recognize insect species in images of sticky traps
Published 2024“…Using a generalised linear model (GLM) and a Boruta feature selection algorithm, we also showed that the colour and architecture of the sticky traps significantly influenced the performance of the model. …”
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Enhancing understanding of programming concepts through physical games
Published 2017“…We produced in total 10 lesson games to illustrate variables, swapping, arrays, sorting algorithm particularly bubble sort, quicksort, selection sort, graph theory, dynamic programming, amortized analysis and trees. …”
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The Identification of High Potential Archers Based on Fitness and Motor Ability Variables: A Support Vector Machine Approach
Published 2018“…Support Vector Machine (SVM) has been shown to be an effective learning algorithm for classification and prediction. …”
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Artificial Intelligence (AI) to predict dental student academic performance based on pre university results
Published 2021“…This study aims to predict the academic performance of dental students based on their admission results using Artificial Intelligence. Machine Learning Algorithm is applied using academic result samples of graduates of the Kulliyyah of Dentistry, IIUM from 2016-2021. …”
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The identification of high potential archers based on relative psychological coping skills variables: a support vector machine approach
Published 2018“…Support Vector Machine (SVM) has been revealed to be a powerful learning algorithm for classification and prediction. …”
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The identification of high potential archers based on relative psychological coping skills variables: A Support Vector Machine approach
Published 2018“…Support Vector Machine (SVM) has been revealed to be a powerful learning algorithm for classification and prediction. …”
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11
Machine Learning Based Two Phase Detection and Mitigation Authentication Scheme for Denial-of-Service Attacks in Software Defined Networks
Published 2024“…This scheme incorporates machine learning techniques by utilizing Support Vector Machine (SVM) and K-Nearest Neighbors (KNN) classification algorithms to accurately identify and handle malicious network traffic following the initial packet filtration process that identifies abnormal traffic. …”
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The employment of support vector machine to classify high and low performance archers based on bio-physiological variables
Published 2018“…The present study employs a machine learning algorithm namely support vector machine (SVM) to classify high and low potential archers from a collection of biophysiological variables trained on different SVMs. 50 youth archers with the average age and standard deviation of (17.0 +/-.056) gathered from various archery programmes completed a one end shooting score test. …”
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The employment of Support Vector Machine to classify high and low performance archers based on bio-physiological variables
Published 2018“…The present study employs a machine learning algorithm namely support vector machine (SVM) to classify high and low potential archers from a collection of bio-physiological variables trained on different SVMs. 50 youth archers with the average age and standard deviation of (17.0 ±.056) gathered from various archery programmes completed a one end shooting score test. …”
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