Search Results - (( using least problem 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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On damping parameters of Levenberg-Marquardt algorithm for nonlinear least square problems
Published 2021“…The Levenberg-Marquardt (LM) algorithm is a widely used method for solving problems related to nonlinear least squares. …”
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Conference or Workshop Item -
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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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Enhancing Market-Based Scheduling Algorithm on Globally Distributed Web Servers Using Least Suitable Sealed Bid Technique
Published 2006“…Scheduling of a multiple distributed servers is considered as a complex problem.considered as NP-complete problem,where no single efficient algorithm guaranteed to produce optimal results.This thesis investigates on how to find optimal solution for distribute system,by implementing market based scheduling Algorithm(MBSA).On implementing the MBSA, a new auction technique which is the least suitable sealed bid auction will be introduced.it is found that least suitable sealed bid technique will give the close-to-optimum solution.In the implementation, cooperative agents were used as a middleware between web servers and stand-alone schedulers. …”
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Thesis -
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Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction
Published 2014“…The lvABC algorithm is introduced to overcome the local optima problem by enriching the searching behaviour using Levy mutation. …”
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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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A hybrid local search algorithm for minimum dominating set problems
Published 2022“…In the first stage, we propose an adaptive information content-based local search algorithm as an exploratory procedure. This algorithm focuses on generating promising solutions in different areas of the solution space using the problem search history. …”
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A hybrid local search algorithm for minimum dominating set problems
Published 2022“…In the first stage, we propose an adaptive information content-based local search algorithm as an exploratory procedure. This algorithm focuses on generating promising solutions in different areas of the solution space using the problem search history. …”
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Least congested channel recommendation for uncoordinated WiFi access point / Ag Ibrahim Ag Daud
Published 2017“…This study has design channel scoring algorithm using Link Score Method, whereby the channel with the highest score were selected as least congested channel (LCC). …”
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Backpropagation algorithm for classification problem: academic performance prediction model for UiTM Melaka Mengubah Destini Anak Bangsa (MDAB) program. / Fadhlina Izzah Saman, Nur...
Published 2012“…Multilayer perceptrons (MLPs) is one of the topology used for processing ANN, while backpropagation algorithm is one of the most popular methods in training MLPs. …”
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Research Reports -
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Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares
Published 2009“…The Ordinary Least Squares (OLS) method is often used to estimate the parameters of a linear model. …”
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Optimization of drilling path using the bees algorithm
Published 2021“…Optimization is the process of finding the best possible solutions to a problem. It has been widely used in various areas especially in engineering problems. …”
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Travelling salesman problem using genetic algorithm / Muhammad Faiz Wafiq Mohd Zaini, Nurin Hannani Mohd Bakhary and Nur Aishah Zakaria
Published 2022“…Travelling Salesmen Problem is a well-known algorithm problem in the fields of computer science and operation research. …”
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