Search Results - (( using simulation cell 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 Collision Detection Algorithm For Virtual Robot-Centered Flexible Manufacturing Cell
Published 2008“…This thesis presents a collision detection algorithm for accurate simulation of a virtual flexible manufacturing cell. …”
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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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Indoor global path planning based on critical cells using dijkstra algorithm
Published 2015“…These critical cells are used as the vertices to the Dijkstra algorithm, with distances between two successive cells as edges between them, and the shortest path between a set of predefined points within the terrain can then be calculated. …”
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…In order to validate the proposed algorithm, a number of experiments using various datasets were conducted and compared the outcomes with different�state-of-the-art algorithms. …”
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Scheduling dynamic cellular manufacturing systems in the presence of cost uncertainty using heuristic method
Published 2016“…Then, design of experiments is used to examine the sensitivity of the parameters of each solving algorithm using Taguchi method. …”
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Dynamic modelling of a two-stage ATM Tandem Banyan Switch / Tham Hon Loke
Published 2002“…The algorithm covers all cell flow patterns that are possible in a 2 Inports x 2 Outports Banyan Switch. …”
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Path planning algorithm for a car-like robot based on cell decomposition method
Published 2013“…Using cell decomposition, the free space of the robot is exactly partitioned into cells. …”
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Comparative analysis of danger theory variants in measuring risk level for text spam messages
Published 2024journal::journal article -
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Application of genetic algorithms to model parameter identification of a recombinant e.coli high-cell density fed-batch fermentation / Kamaruddin Mamat and Farida Zuraina Mohd Yuso...
Published 2008“…In this work, a genetic algorithm was used to estimate both yield and kinetic coefficients of an unstructured model representing a fed-batch high-cell density fermentation of Escherichia coli (E. coli). …”
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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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Hybrid artificial intelligent algorithm for call admission control in WCDMA mobile network
Published 2023“…The proposed algorithm, support vector regression assists genetic algorithm (SVRaGA) was tested in a dynamic WCDMA mobile network simulator. …”
Conference paper -
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Application of genetic algorithms to model parameter identification of a recombinant e.coli high-cell density fedbatch fermentation / Kamaruddin Mamat and Farida Zuraina Mohd Yusof
Published 2008“…In this work, a genetic algorithm was used to estimate both yield and kinetic coefficients of an unstructured model representing a fed-batch high-cell density fermentation of Escherichia coli (E.coli). …”
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DSP controlled isolated DC-DC converter for distributed generation system
Published 2023“…Digital Signal Processing (DSP) board is used to implement the control algorithm. The control algorithm includes phase-shift PWM and PID close loop control, are designed using SIMULINK Embedded Target Library which are used to represent algorithms and peripherals specific DSP family. …”
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