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1
Driver behaviour classification: a research using OBD-II data and machine learning
Published 2024“…The suggested model in this study analyses driving behaviour using both supervised and unsupervised methods. The relationship between all features and engine speed is analysed to select the optimal features, which include engine speed, vehicle speed, throttle position, and calculated engine load. …”
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2
Detection and classification of conflict flows in SDN using machine learning algorithms
Published 2021“…Moreover, applying machine learning algorithms in the identification and classification of conflicting flows has limitations. …”
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An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM)
Published 2024“…This study recommends a selection trade-off as the function of prediction efficiency and efficacy of the algorithm. Particularly, the proposed optimized Bagged Trees are the most effective algorithm for energy demand prediction applications, and the proposed optimized Medium Trees are the most efficient algorithm for real-time systems. …”
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4
Decision tree-based approach for online management of PEM fuel cells for residential application
Published 2004“…In this research, a Decision Tree (DT) algorithm is employed to obtain the optimal, or quasioptimal, settings of the fuel cell online and in a general framework. …”
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5
Decision tree-based approach for online management of pem fuel cells for residential application
Published 2004“…In this research, a Decision Tree (DT) algorithm was employed to obtain the optimal, or quasi-optimal, settings of the fuel cell online and in a general framework. …”
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6
Application of genetic algorithm methods to optimize flowshop sequencing problem
Published 2008“…Genetic algorithm method was one of the methods that were widely used in solving optimization problem. …”
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Undergraduates Project Papers -
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Cyberbullying detection: a machine learning approach
Published 2022“…The machine learning algorithm, Support Vector Machine was chosen after comparing it with other algorithms such as Multinomial Naïve Bayes, Decision Tree Classifier, and Random Forest Classifier. …”
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Final Year Project / Dissertation / Thesis -
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Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan
Published 2018“…Later, an Iterative-based Sizing Algorithm (ISA) was developed to determine the optimal sizing solution which was later used as benchmark for sizing algorithms using optimization methods. …”
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9
An improved method using fuzzy system based on hybrid boahs for phishing attack detection
Published 2022“…Moreover, Butterfly Optimization Algorithm and Harmony Search Algorithm were combined as optimization method led to a new method named BOAHS. …”
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10
Ganoderma boninense classification based on near-infrared spectral data using machine learning techniques
Published 2022“…A PLS regression is used on NIR spectra to implement the prediction of ergosterol concentration which shows good corelation of R = 0.861 between the ergosterol concentration and oil palm NIR spectra. Four different ML algorithms are tested for prediction of G. boninense infection: K-Nearest Neighbour (kNN), Naïve Bayes (NB), Support Vector Machine (SVM) and Decision Tree (DT) are tested which depicted DT algorithm achieves a satisfactory overall performance with high accuracy up to 93.1% and F1-score of 92.6% compared to other algorithms. …”
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Wind farm reactive power optimization by using imperialist competitive algorithm
Published 2013“…In this paper a new evolutionary computing method based on imperialist competitive algorithm (ICA) is used for optimization of the reactive power in a wind farm. …”
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Conference or Workshop Item -
12
SA-EVPS ALGORITHM FOR DISCRETE SIZE OPTIMIZATION OF THE 582-BAR SPATIAL TRUSS STRUCTURE
Published 2023“…Nowadays, approximate optimization methods are widely used. This study utilized the Self Adaptive Enhanced Vibrating Particle System (SA-EVPS) algorithm as an approximate optimization method, since the EVPS algorithm requires experimental parameters. …”
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VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern
Published 2012“…Two methods of optimization are used for CBLL. They are Cross Entropy and also Genetic Algorithm. …”
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14
Wind Farm Reactive Power Optimization by Using Imperialist Competitive Algorithm
Published 2013“…In this paper a new evolutionary computing method based on imperialist competitive algorithm (ICA) is used for optimization of the reactive power in a wind farm. …”
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Conference or Workshop Item -
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Firefly algorithm for optimal sizing of Standalone Photovoltaic System / Nurizzati Abdul Aziz
Published 2016“…Therefore, optimization methods are often used in the sizing algorithms for such systems. …”
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Firefly algorithm for optimal sizing of stand-alone photovoltaic system / Nur Izzati Abdul Aziz
Published 2016“…Therefore, optimization methods are often used in the sizing algorithms for such systems. …”
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17
Optimization Of Bar Linkage By Using Genetic Algorithms
Published 2005“…This thesis presents the method of using simple Genetic Algorithms (GAs) in optimizing the size of bar linkage with discrete design variables and continues design variables. …”
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Monograph -
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Route optimization using shortest path method / Muhamad Faisal Amin Shakri
Published 2025“…Therefore, the effectiveness of route planning is very essential. The method to study route optimization is called shortest path method. …”
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19
A firefly algorithm based hybrid method for structural topology optimization
Published 2020“…In this paper, a firefly algorithm based hybrid algorithm through retaining global convergence of firefly algorithm and ability to generate connected topologies of optimality criteria (OC) method is proposed as an alternative method to solve stress-based topology optimization problems. …”
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Multi-Objective Portfolio Optimization Strategy using the SPEA-II Algorithm
Published 2025“…Realistic constraints are applied to formulate a multi-objective optimization problem. SPEA-II and traditional multi-objective optimization methods are used to solve this problem, resulting in a set of optimal portfolios. …”
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