Search Results - (( evolution optimisation based algorithm ) OR ( data application testing 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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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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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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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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Fsm-Based Enhanced March C- Algorithm For Memory Built-In Self-Test
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Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection
Published 2015“…However the average classification accuracy of 84.74% on the unseen test data did not achieve the acceptable average success rate of 90% in this application. …”
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ANALYSIS AND INTERPRETATION OF PRESSURE TRANSIENT TEST DATA BY RECENT ROBUST DECONVOLUTION METHODS
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Final Year Project -
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Fault detection with optimum March test algorithm
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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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Randomness Tests On Nine Data Categories Of RECTANGLE Using NIST Statistical Test Suite
Published 2024Article -
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Diabetes prediction system using clonal selection algorithm / Nor Aishah Mustapa
Published 2012“…The data included in the system is a tested and accurate data. …”
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Parallelization of noise reduction algorithm for seismic data on a beowulf cluster
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