Search Results - (( using action problems algorithm ) OR ( evolution optimisation based algorithm ))
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Performance evaluation and benchmarking of an extended computational model of ant colony system for DNA sequence design
Published 2014“…Ant colony system (ACS) algorithm is one of the biologically inspired algorithms that have been introduced to effectively solve a variety of combinatorial optimisation problems. …”
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A competitive co-evolutionary approach for the nurse scheduling problem
Published 2026“…The competitive approach further exhibits smoother convergence behaviour across generations, indicating stronger optimisation dynamics and improved robustness. These findings demonstrate that competitive co-evolution provides an effective and practical alternative to static fitness-based evolutionary methods for nurse scheduling, with broader applicability to healthcare scheduling and constraint optimisation problems.…”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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Stock market turning points rule-based prediction / Lersak Photong … [et al.]
Published 2021“…Finally, rule-based optimisation techniques such as Particle Swarm Optimization (PSO), Differential Evolution (DE) and Grey Wolf Optimizer (GWO) were used to minimise the amount of time employed in the stock market turning points prediction. …”
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Book Section -
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Knowledge base tuning using genetic algorithm for fuzzy behavior-based autonomous mobile robot
Published 2005“…This control architecture should generate perfect behavior action and able to handle conflicting actions that are seemingly irreconcilable, those are known as Behaviour Design Problem and Action Selection Problem. …”
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Conference or Workshop Item -
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B-spline curve fitting with different parameterization methods
Published 2020“…After generating control points, distance between the generated and original data points is used to identify the error of the algorithm. Later, genetic algorithm and differential evolution optimization are used to optimise the error of the curve. …”
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Final Year Project / Dissertation / Thesis -
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Enhanced Adaptive Confidence-Based Q Routing Algorithms For Network Traffic
Published 2004“…In CQ Routing Algorithm, the confidence value (C value) can be used to improve the quality of exploration in Q Routing Algorithm. …”
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Reliability assessment of power system generation adequacy with wind power using population-based intelligent search methods
Published 2017“…This study sought to examine the performance of three newly proposed techniques, for reliability assessment of the power systems, namely Disparity Evolution Genetic Algorithm (DEGA), Binary Particle Swarm Optimisation (BPSO), and Differential Evolution Optimization Algorithm (DEOA). …”
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Thesis -
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Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level
Published 2024thesis::doctoral thesis -
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An interactive analytics approach for sustainable and resilient case studies: a machine learning perspective
Published 2023“…To show the methods applicability, this paper uses the proposed algorithm in three sustainable and resilient case studies. …”
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A novel deadlock detection algorithm for neighbour replication on grid environment
Published 2012“…Therefore, an action must be taken to detect and solve this problem. …”
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Thesis -
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Algorithm As A Problem Solving Technique For Teaching And Learning Of The Malay Language
Published 2019“…Computational thinking or CT refers to the thought processes involved in expressing solutions as computational steps or algorithms that can be carried out by a computer. CT is not merely using software or computer programs alone but is also interlinked with information and communication technology (ICT) and computer science based on problems; tools; action (praxis); solutions; concepts; and social needs. …”
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A new ant based rule extraction algorithm for web classification
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Monograph -
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Pengoptimuman algoritma pengesanan batu loncatan dalam sistem pengesanan pencerobohan
Published 2005“…Previous researches have used some approaches like intelligent agent and IDS adoption to solve time gap problem. …”
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Thesis -
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iBUST: An intelligent behavioural trust model for securing industrial cyber-physical systems
Published 2024“…In addition, a new optimisation model for finding optimum parameter values in the MEDF and an algorithm for transmuting a 1D quantitative feature into a respective categorical feature are developed to facilitate the model. …”
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Algorithm as a problem solving technique for teaching and learning of the Malay language
Published 2019“…Computational thinking or CT refers to the thought processes involved in expressing solutions as computational steps or algorithms that can be carried out by a computer. CT is not merely using software or computer programs alone but is also interlinked with information and communication technology (ICT) and computer science based on problems; tools; action (praxis); solutions; concepts; and social needs. …”
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The effectiveness of using the Lattice in multiplication skills among Year 5 in SK Beradek / Muhamad Shaharudin Muhamad Sarip
Published 2015“…This study was conducted based on Kurt Lewin's research model involves five main steps of identifying aspects of practice, designing an action plan, implementing the plan of action, the effect of the action, and reflection on all the action. …”
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Thesis -
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Newton competitive genetic algorithm method for optimization the production of biochemical systems
Published 2018“…To deal with the problem, this work proposed a hybrid method of the Newton method, genetic algorithm, and competitive co-evolutionary algorithm. …”
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