Search Results - global optimisation ((method algorithm) OR (based algorithm))
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Bats echolocation-inspired algorithms for global optimisation problems
Published 2016“…The works related to swarm intelligence algorithms include the development of the algorithm itself, its modification and improvisation as well as its application in solving global optimisation problems. …”
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Aco-based feature selection algorithm for classification
Published 2022“…The modified graph clustering ant colony optimisation (MGCACO) algorithm is an effective FS method that was developed based on grouping the highly correlated features. …”
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Improvement Of Stereo Matching Algorithm Based On Sum Of Gradient Magnitude Differences And Semi-Global Method With Refinement Step
Published 2018“…A new stereo matching algorithm which uses improved matching cost computation and optimisation using the semi-global method (SGM) is proposed.The absolute difference is sensitive to low textured regions and high noise on the stereo images with radiometric distortions. …”
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An improved particle swarm optimization algorithm for data classification
Published 2023“…Particle Swarm Optimization (PSO) is a metaheuristic algorithm based on swarm intelligence, widely used to solve global optimisation problems throughout the real world. …”
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Enhanced convergence of Bat Algorithm based on dimensional and inertia weight factor
Published 2019“…Heuristic optimisation method typically hinges on the efficiency in exploitation and global diverse exploration. …”
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Image segmentation based on normalised cuts with clustering algorithm
Published 2013“…Clustered segments from the local segmentation are then used for image segmentation in global perspective. As the clusters initialisation gives influence to the segmentation result, optimisation of the clustering algorithm is implemented to achieve a better segmentation. …”
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Selective harmonic elimination in multilevel inverter using hybrid APSO algorithm
Published 2018“…In the proposed method, ring topology-based APSO algorithm is hybrid with NR method. …”
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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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Local-based stereo matching algorithm using multi-cost pyramid fusion, hybrid random aggregation and hierarchical cluster-edge refinement
Published 2023“…Similar to how human eyes and binocular vision perceive depth, the visual disparity information obtained from this pair of images captured by the cameras represents the impression of perceived depth. The stereo vision algorithm computes disparity using local, global, and semiglobal optimisation methods established by the researcher. …”
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Optimised multi-robot path planning via smooth trajectory generation
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Final Year Project / Dissertation / Thesis -
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Optimisation of support vector machine hyperparameters using enhanced artificial bee colony variant to diagnose breast cancer
Published 2023“…The performance of SVM can be affected by hyperparameters, which are kernel scale and known as gamma and regularization parameters (C). A metaheuristic algorithm is introduced to optimise the hyperparameters. …”
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Investigating The Performance Of Metaheuristics To Optimize The Revenue Of Semiconductor Supply Chain
Published 2022“…Investigating the performance of metaheuristics to optimise the revenue of the semiconductor supply chain is the final year project that focuses on to identify the supply chain shortage problem related to semiconductors and to compare among the 20 metaheuristics algorithm optimization programmes capable of optimising the semiconductor supply chain. …”
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Data-driven hybrid approaches for renewable power prediction toward grid decarbonization: Applications, issues and suggestions
Published 2023“…Decarbonization; Electric power transmission networks; Forecasting; Fossil fuels; Global warming; Solar energy; Data driven; Data-driven algorithm; Data-driven approach; Data-driven methods; Decarbonisation; Hybrid approach; Hybrid datum; Optimisations; Power predictions; Renewable Power; Wind power…”
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Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse)
Published 2015“…The hybrid of Differential Evolution algorithm with Kalman Filtering and Bacterial Foraging algorithm is a novel global optimisation method implemented to obtain the best kinetic parameter value. …”
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The Bacterial Foraging Optimisation Algorithm using Prototype Selection and Prototype Generation for Data Classification
Published 2020“…A new emerging nature-inspired algorithm named Bacterial Foraging Optimisation Algorithm (BFOA) that mimics the foraging behaviour of E. coli bacteria has drawn lots of attention from other researchers due to its high convergence rate and global search capability compared to others. …”
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Thesis