Search Results - (( evolution optimisation based algorithm ) OR ( using action method 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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Book Section -
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STUDIES ON COMPARISON OF PROPORTIONAL ON ERROR WITH PROPORTIONAL ON MEASURED VALUE IN PID CONTROLLERS
Published 2019“… PID Controllers have different algorithms or methods in which the controller action is based on Error or Process Variable (PV). …”
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Final Year Project -
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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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Thesis -
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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 Improved Action Key Frames Extraction Algorithm for Complex Colour Video Shot Summarization
Published 2019“…We then evaluated the Improved AKF algorithm with the-state-of-the-art algorithms in terms of compression ratio using Paul videos and Shih-Tang dataset. …”
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Revolutionizing video analytics: a review of action recognition using 3D
Published 2024“…As an interdisciplinary field, the 3D video action recognition model interprets human actions in three-dimensional video data using approaches such as pose-based, volumetric, motionbased, and hybrid methods. 3D video action recognition finds application in surveillance, sports analysis, human-computer interaction, healthcare, robotics, and augmented/virtual reality. …”
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Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof
Published 2019“…From the reviews, it is evident that autonomous system is set to handle finite number of encountered states using finite sequences of actions. In order to learn the optimized states-action policy the self-learning algorithm is developed using hybrid AI algorithm by combining unsupervised weightless neural network, which employs AUTOWiSARD and reinforcement learning algorithm, which employs Q-learning. …”
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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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Simulation of an adaptive artificial neural network for power system security enhancement including control action
Published 2015“…This paper presents a new method for enhancing power system security, including a remedial action, using an artificial neural network (ANN) technique. …”
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A new ant based rule extraction algorithm for web classification
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Monograph -
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Particle swarm optimization with deep learning for human action recognition
Published 2021“…This paper proposes a deep learning framework for human action recognition to overcome the drawbacks of the current state-of-the-art methods. …”
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Adaptive artificial neural network for power system security assessment and control action
Published 2012“…This is particularly important for giving a possible control action to mitigate an insecure situation during disturbance using AANN. …”
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Thesis -
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Newton competitive genetic algorithm method for optimization the production of biochemical systems
Published 2018“…In this work, the optimization of biochemical systems production is performed by using a hybrid method of Newton competitive genetic algorithm is presented. …”
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Property premises intruders detection using face recognition method / Joveni Henry
Published 2017“…Every property premises owner have already taken some action to protect their property premises and safety by using all kinds of methods. …”
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Thesis
