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Particle Swarm Optimization in Machine Learning Prediction of Airbnb Hospitality Price Prediction
Published 2022“…Particle Swarm Optimization is useful to optimize the best variables combination for automating the features selection in machine learning models. …”
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Examining the potential of machine learning for predicting academic achievement: A systematic review
Published 2023“…Predicting student academic performance is a critical area of education research. Machine learning (ML) algorithms have gained significant popularity in recent years. …”
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Examining the potential of machine learning for predicting academic achievement: A systematic review
Published 2023“…Predicting student academic performance is a critical area of education research. Machine learning (ML) algorithms have gained significant popularity in recent years. …”
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The Determinant Factors for the Issuance of Central Bank Digital Currency (CBDC) in Malaysia using Machine Learning Framework
Published 2024“…The overall CentralBank Digital Currency Project Index (CBDCPI) was selected as a target variable,while two machine learning algorithms, Random Forest and XGBoost were utilized to identify the determining variables. …”
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RSA Encryption & Decryption using JAVA
Published 2006“…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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Final Year Project -
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Provider independent cryptographic tools
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Monograph -
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Empirical Analysis of Intra vs. Inter-Subject Variability in VR EEG-Based Emotion Modelling
Published 2018“…These methods showed highly promising results and will be further enhanced using other machine learning approaches such as deep learning in VR stimulus.…”
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The determinant factors for the issuance of Central Bank Digital Currency (CBDC) in Malaysia using machine learning framework
Published 2024“…The overall Central Bank Digital Currency Project Index (CBDCPI) was selected as a target variable, while two machine learning algorithms, Random Forest and XGBoost were utilized to identify the determining variables. …”
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Machine Learning in Sports: Identifying Potential Archers
Published 2019“…This brief highlights the association of different performance variables that influences archery performance and the employment of different machine learning algorithms in the identification of potential archers. …”
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Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management
Published 2024“…Particle Swarm Optimization (PSO) has demonstrated its efficacy in addressing the issue of construction waste reduction and enhancing the accuracy of cost estimation through the identification of optimal combinations of variables. …”
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Green building valuation based on machine learning algorithms / Thuraiya Mohd ... [et al.]
Published 2021“…In the cycle of Industrial Revolution 4.0 (IR 4.0), many issues in the industries can be solved with implementation of artificial intelligence approaches, including machine learning models. …”
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Conference or Workshop Item -
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Automated model selection for corporation credit risk assessment using machine learning / Zulkifli Halim
Published 2023“…This study has proposed an automated model selection based on the exhaustive search algorithm—that caused the timeout and memory leak issues. …”
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Crossover and mutation operators of genetic algorithms
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Crossover and mutation operators of genetic algorithms
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Tangible interaction learning model to enhance learning activity processes among children with dyslexia
Published 2024“…To find optimum variables, Machine Learning approach needs to be utilized. …”
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Synchronizing Artificial Intelligence Models for Operating the Dam and Reservoir System
Published 2018“…Therefore, operating the reservoir system is complex issue due to existing the nonlinearity hydrological variables. …”
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An application of predicting student performance using kernel k-means and smooth support vector machine
Published 2012“…In this study, psychometric factors used as predictor variables, thereare Interest, Study Behavior, Engaged Time, Believe, and Family Support.The rulemodel developed using Kernel K-means Clustering and Smooth Support Vector MachineClassification.Both of these techniquesbased on kernel methodsand relativelynew algorithms of data mining techniques, recently received increasingly popularity in machine learning community. …”
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Thesis
