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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…All the algorithm for the engine has been developed by using Java script language. …”
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2
Dual-head marking performance optimisation via evolutionary solutions
Published 2023“…This paper presents a new approach to optimise the performance of a multi-head marking system in terms of its marking speed This processing method named as MMA (Molecular Marking Optimisation algorithm) will adopt the use of Genetic Algorithm. …”
Conference paper -
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Optimisation of vehicle routing problem with time windows using Harris Hawks optimiser
Published 2022“…This problem has been widely studied and optimised using different methods. Since the performance of algorithms in different problems is dissimilar, the study to optimise the VRPTW is ongoing. …”
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Optimisation of fed-batch fermentation process using deep reinforcement learning
Published 2023“…Deep reinforcement learning is a self-learning algorithm through trial and error and experience, without any prior knowledge. …”
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Evaluating JA-ABC5 hyperparameter optimisation with classifiers
Published 2024“…The Wisconsin dataset is used to evaluate the performance of these classifiers, and the hyperparameters are optimised using the JA-ABC5 algorithm. …”
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Hybrid genetic algorithm for uncapacitated university examination timetabling problem
Published 2015“…All proposed algorithms are coded in C using Microsoft Visual C++ 6.0 as the compiler. …”
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8
A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks / Salmah Fattah
Published 2022“…Next, it establishes the research problems by implementing various existing algorithms using comparative analysis. Based on that analysis, this research suggests a hybrid algorithm: the Multi-Objective Optimisation Genetic Algorithm based on Adaptive Multi-Parent Crossover and Fuzzy Dominance (MOGA-AMPazy). …”
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A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks
Published 2022“…Next, it establishes the research problems by implementing various existing algorithms using comparative analysis. Based on that analysis, this research suggests a hybrid algorithm: the Multi-Objective Optimisation Genetic Algorithm based on Adaptive Multi-Parent Crossover and Fuzzy Dominance (MOGA-AMPazy). …”
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Hybrid genetic algorithm for university examination timetabling problem
Published 2016“…These new local optimisation techniques will arrange the timeslots and exams using new explicit equations, if and only if, the modification will reduce the penalty cost function. …”
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Article -
12
Kernel and multi-class classifiers for multi-floor wlan localisation
Published 2016“…The multi-class classification strategy is used to ensure quick estimation of the multi-class NN algorithms. …”
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13
Optimal route checking using genetic algorithm for UiTM's bus services / Tengku Salman Fathi Tengku Jaafar
Published 2006“…Although from human logical thinking, the route can be generated easily but the calculation of checking the route whether it is optimal route or not is difficult and will take long time to be implemented. This research study with the development of the Optimal Route Checking Using Genetic Algorithm system should solve this scenario. …”
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14
Multi-Objective Optimisation of CNC Milling Process for Al 6061 using Modified NSGA-II
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Meta-heuristic approaches for reservoir optimisation operation and investigation of climate change impact at Klang gate dam
Published 2023“…Consequently, seeking managing of reservoir optimisation operations had always been at the forefront and to improve managing, algorithms have had been presented over the past few decades, beginning with conventional algorithms, followed by heuristic algorithms, and finally, the meta-heuristic algorithms (MHAs). …”
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Final Year Project / Dissertation / Thesis -
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Locust- inspired meta-heuristic algorithm for optimising cloud computing performance
Published 2023“…This algorithm can also be used for task scheduling. The proposed algorithm efficiently maps and achieves the objective function for server consolidation, optimising energy consumption, VM migrations, and server utilisation. …”
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Parametric modelling of a TRMS using dynamic spread factor particle swarm optimisation
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Proceeding Paper -
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A framework of test case prioritisation in regression testing using particle swarm-artificial bee colony algorithm
Published 2024“…TCP factors and a weighted fitness function are also used for test case optimisation. The contributions of this study straddle research perspectives of enhancing Regression Testing with Particle Swarm-Artificial Bee Colony Algorithm, and practical perspectives by providing software testing practitioners the TCP framework that can facilitate and accelerate the production of high-quality software products by revealing faults early and reducing time, cost, and human efforts through automation.…”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…The system trains the NN on previously labelled data, and its knowledge is used to calculate the core online-offline clustering block error. …”
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