Search Results - (( rendering optimization based algorithm ) OR ( basic optimisation _ algorithm ))
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Enhanced convergence of Bat Algorithm based on dimensional and inertia weight factor
Published 2019“…Benchmark test function is then performed for the basic Bat Algorithm and the modified Bat Algorithm (MBA) for comparison. …”
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Develpoment of combinatorial optimisation for cutting tool path strategy
Published 2009“…This work aims to optimise the tool path by simulating the removal of material in a finite element environment, which is controlled by a Genetic Algorithm. …”
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Dynamic Economic Dispatch For Large Scale Power Systems: A Lagrangian Relaxation Approach
Published 1991“…Otherwise, Dantzig-Wolfe decomposition is invoked, using almost all the information generated during subgradient optimization to ensure a speedy conclusion. The computational efficiency of the algorithm renders it suitable for on-line dispatch.…”
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Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud
Published 2023“…The pandemic has resulted in unpredictable customers’ purchasing patterns post-pandemic has rendered heuristic-based forecasting large forecast errors, which leads to poor decision-making. …”
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An experimental validation and optimisation tool path strategy for thin walled structure
Published 2011“…This work was carried out with the aim to optimise the tool path by simulating the removal of material in a finite element environment which is controlled by a genetic algorithm (GA). …”
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Integration of simulation for ergonomics assessment in operation control centre (railway industries) / Adib Zulfadhli Mohd Alias
Published 2019“…This study will focus on the translation of the CAD/Revit model into simulation software, either directly or through the intermediate stage of rendering package. Complete CAD/Revit model can be used to generate simulation model by straight forward translation of the whole model or with the algorithms for optimization. …”
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Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm
Published 2025“…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm
Published 2025“…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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Evaluating the Efficacy of Intelligent Methods for Maximum Power Point Tracking in Wind Energy Harvesting Systems
Published 2024“…Furtherly, Artificial Intelligence (AI)-based MPPT algorithms were proposed for the WEHS as either standalone or integrated with the traditional MPPT methods. …”
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Development of intelligent evaluation system for product end-of-life selection strategy
Published 2011“…This study integrates the travelling salesman problem with genetic algorithm (TSP-GA) for finding the optimal disassembly sequence and disassembling the EOL product. …”
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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 search manoeuvres recruitment in the bees algorithm
Published 2011“…Swarm intelligence of honey bees had motivated many bioinspired based optimisation techniques. The Bees Algorithm (BA) was created specifically by mimicking the foraging behavior of foraging bees in searching for food sources.During the searching, the original BA ignores the possibilities of the recruits being lost during the flying.The BA algorithm can become closer to the nature foraging behavior of bees by taking account of this phenomenon.This paper proposes an enhanced BA which adds a neighbourhood search parameter which we called as the Local Search Manoeuvres (LSM) recruitment factor.The parameter controls the possibilities of a bee extends its neighbourhood searching area in certain direction.The aim of LSM recruitment is to decrease the number of searching iteration in solving optimization problems that have high dimensions.The experiment results on several benchmark functions show that the BA with LSM performs better compared to the one with basic recruitment.…”
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Handover Parameter for Self-optimisation in 6g Mobile Networks: A Survey
Published 2024journal::journal article -
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Unit commitment in power system using multi-agent evolutionary programming incorporating priority listing optimisation technique / Muhammad Nazree Che Othman
Published 2013“…The developed technique was tested on the 10 generating units test system then up to 20 generating units in a 24-hours scheduling period and the results was compared with the basic EP, Evolutionary Programming with Priority Listing (EP-PL) and Multi-agent Evolutionary Programming (MAEP) optimisation techniques. …”
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Augmented Reality Framework For Symbian Mobile Devices
Published 2013“…Open source libraries such as OpenGL and OpenCV are used to develop mobile AR framework. Optimized algorithms are used to ensure that AR application running smooth. …”
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Intelligent traffic lights using Q-learning
Published 2022“…Q-learning derives benefits from past experiences and determines the optimal course of action based on them. The performance of the proposed system has been measured against that of the traditional system, which is a fixed time cycle system. …”
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Proceeding Paper -
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Cuckoo optimised 2DOF controllers for stabilising the frequency changes in restructured power system with wind-hydro units
Published 2021“…Different types of metaheuristic optimisation methods like teaching–learning-based optimisation (TLBO) and cuckoo search algorithms are suggested to acquire the optimal gain values of the proposed controllers. …”
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