Search Results - (( initial solution matching algorithm ) OR ( evolution optimisation based algorithm ))
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Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman
Published 2019“…In this HPSO algorithm, totally seven particles positions are initialized. …”
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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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Hybrid dynamic scheduling model for flexible manufacturing system with machine availability and new job arrivals
Published 2015“…The BBO-VNS match-up algorithm manipulates the idle times on machines within the time horizon for assigning the affected operations by breakdown and/or newly arrived orders. …”
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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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On the spectra efficiency of low-complexity and resolution hybrid precoding and combining transceivers for mmWave MIMO systems
Published 2019“…Then adds a pruning step −after satisfying a sparsity level condition, to iteratively refine the sparse solution which aids in further accelerating the algorithm, by requiring fewer iterations. …”
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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…Experimental results show that EACO produced better grid resource management solution compared to other algorithms. …”
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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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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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Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level
Published 2024thesis::doctoral thesis -
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An advanced scheme based on Artificial Intelligence technique for solving nonlinear Riccati systems
Published 2024“…Numerical results demonstrate that the proposed method not only closely matches the exact solutions and reference solutions but also is more accurate than other existing methods. © The Author(s) under exclusive licence to Sociedade Brasileira de Matemática Aplicada e Computacional 2024.…”
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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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Cars detection in stitched image using morphological approach
Published 2017“…The performance of the proposed cars detection algorithm could detect the cars fairly accurate. In addition, this project could be a solution to detect trapped cars in a flood to provide useful information to the rescue department where the image sequences of the flood scene could be stitched together to get a wider view of the flood without zooming the view of the scene to get the whole view of the flood. …”
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Final Year Project Report / IMRAD -
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A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat
Published 2021“…The iterative nature of KMeans and random initialization of centroids which leads the algorithm to stick in a local optimum and unable to converge to optimum results, are another weakness. …”
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A self‐configured link adaptation for green LTE downlink transmission
Published 2015“…Current and next‐generation cellular networks require such interactive techniques in order to be self‐optimised without complex modifications.…”
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