Search Results - (( based optimisation based algorithm ) OR ( basic optimization based algorithm ))
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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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Conference or Workshop Item -
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Parametric modelling of a TRMS using dynamic spread factor particle swarm optimisation
Published 2009“…In this paper, a sound approach for a Twin Rotor Multi-input Multi-Output System (TRMS) parametric modeling is proposed based on dynamic spread factor particle swarm optimization. …”
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Proceeding Paper -
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Handover Parameter for Self-optimisation in 6g Mobile Networks: A Survey
Published 2024journal::journal article -
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Gravitational energy harvesting system based on multistage braking technique for multilevel elevated car parking building
Published 2020“…The results showed that, 34.09% energy and 6.58% delay time have been improved using the proposed system and proposed optimised mass at 3.5 kg. Based on the MSBS experiment, the parameters used are being applied in developing an optimization model; both results are compared and obtained an 8.2% error. …”
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Optimization Of Pid Controller Using Grey Wolf Optimzer And Dragonfly Algorithm
Published 2018“…The expected result is the algorithms are able to optimise the PID controller. …”
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Monograph -
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Intergrated multi-objective optimisation of assembly sequence planning and assembly line balancing using particle swarm optimisation
Published 2013“…The aim of this research is to establish a methodology and algorithm for integrating ASP and ALB optimisation using Particle Swarm Optimisation. …”
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Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…Many optimisation-based intrusion detection algorithms have been developed and are widely used for intrusion identification. …”
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Chaotic Immune Symbiotic Organisms Search algorithm for solving optimisation problem
Published 2023“…Heuristics-based algorithms were introduced to counter the problem faced by classical optimisation techniques. …”
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Bats echolocation-inspired algorithms for global optimisation problems
Published 2016“…The algorithm is a hybrid algorithm that operates using dual level search strategy that takes merits of a particle swarm optimisation algorithm and a modified adaptive bats sonar algorithm. …”
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Aco-based feature selection algorithm for classification
Published 2022“…The modified graph clustering ant colony optimisation (MGCACO) algorithm is an effective FS method that was developed based on grouping the highly correlated features. …”
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Application of the bees algorithm for constrained mechanical design optimisation problem
Published 2019“…Nowadays, many optimisation algorithms have been introduced due to the advancement of technology such as Teaching Learning Based Optimisation (TLBO), Ant Colony Optimisation (ACO), Particle Swarm Optimisation (PSO) and the Bees Algorithm. …”
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Evaluation of Vector Evaluated Particle Swarm Optimisation Enhanced with Non-dominated Solutions and Multiple Nondominated Leaders based on WFG Test Functions
Published 2014“…The improved VEPSO algorithms have been subjected to a series of numerical experiments based on ZDT benchmark datasets. …”
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Metaheuristic algorithms applied in ANN salinity modelling
Published 2024“…The CPSOCGSA performance was evaluated by various single-based ones, including multi-verse optimiser (MVO), marine predator's optimisation algorithm (MPA), particle swarm optimiser (PSO), and the slim mould algorithm (SMA). …”
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Optimal power flow based on fuzzy linear programming and modified Jaya algorithms
Published 2017“…In the proposed novel QOJaya algorithm, an intelligence strategy, namely, quasi-oppositional based learning (QOBL) is incorporated into the basic Jaya algorithm to enhance its convergence speed and solution optimality. …”
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Abnormal event detection in video surveillance / Lim Mei Kuan
Published 2014“…Therefore, by considering tracking as an optimisation problem, the proposed SwATrack algorithm searches for the optimal distribution of motion model without making prior assumptions, or prior learning of the motion model. …”
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