Search Results - (( variable optimisation system algorithm ) OR ( evolution optimization mining algorithm ))
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ENGINEERING DESIGN WITH PSO ALGORITHM
Published 2019“…To optimise a mechanical design by the means of distance or even shape, it needs to these handle large numbers of variables, and optimal solution is needed to for such systems. …”
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Final Year Project -
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Y-type Random 2-satisfiability In Discrete Hopfield Neural Network
Published 2024“…During the retrieval phase, a new activation function and Swarm Mutation were proposed to ensure the diversity of the neuron states. The proposed algorithm and mutation mechanism showed optimal performances as compared to the existing algorithms. …”
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Thesis -
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Published 2019“…A new self-adaptive hybrid algorithm (CSCMAES) is introduced for optimization. …”
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Thesis -
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Seed disperser ant algorithm for optimization / Chang Wen Liang
Published 2018“…The Seed Disperser Ant Algorithm (SDAA) is developed based on the evolution or expansion process of Seed Disperser Ant (Aphaenogaster senilis) colony. …”
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Thesis -
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Hybrid evolutionarybarnacles mating optimisation-artificial neural network based technique for solving economic power dispatch planning and operation / Nor Laili Ismail
Published 2024“…In this study, a new optimisation algorithm termed Hybrid Evolutionary-Barnacles Mating Optimisation (HEBMO) was initially formulated to solve optimisation problems. …”
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Thesis -
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Analyzing The Potential Of Genetic Algorithm For Maximum Power Point Tracking In Wind Energy Conversion System In Malaysia
Published 2023“…In this paper, a maximum power point tracking for the wind turbine is proposed which is the indirect speed control. A genetic algorithm is used to further optimised the control strategy by finding the optimised variable for the controller. …”
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FPGA implementation of simulated kalman filter optimization algorithm
Published 2018“…This paper presents a novel FPGA implementation of the Simulated Kalman Filter Optimisation Algorithm. This system utilizes a distributed RAM to update the intermediate variables and the output of each iteration is stored in the block RAM. …”
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A bacteria foraging algorithm for solving integrated multi-period cell formation and subcontracting production planning in a dynamic cellular manufacturing system
Published 2011“…In addition, a newly-developed BFA-based optimisation algorithm has been compared with the branch and bound algorithm. …”
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Classification with degree of importance of attributes for stock market data mining
Published 2004“…The experimental results show that predictive FDT algorithm can generate a relatively optimal tree without much computation effort (comprehensibility), and WFPRs have a better predictive accuracy of stock market time series data. …”
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On the optimal control of the steel annealing processes as a two-stage hybrid systems via PSO algorithms
Published 2009“…The heating and soaking furnaces of the steel annealing line form the two-stage hybrid systems. Three algorithms including particle swarm optimisation (PSO) with globally and locally tuned parameters (GLBest PSO), a parameter free PSO algorithm (pf-PSO) and a PSO-like algorithm via extrapolated PSO (ePSO) are considered to solve this optimal control problem for the two-stage steel annealing processes (SAP). …”
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Passive congregation theory for particle swarm optimization (PSO): An application in reservoir system operation
Published 2023“…The passive congregation theory of natural being's social behaviour is adopted to updated the standard PSO algorithm and used to develop and optimise a reservoir release policy for monthly basis. …”
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Multivariable adaptive lyapunov fuzzy controller for pH neutralisation process
Published 2015“…In this study, the nominal neutralisation process condition exhibit nonlinear dynamics and multi-delayed-effects input variables. The proposed controller uses a Takagi-Sugeno fuzzy inference system and it has been optimised by genetic algorithm which minimizing the closed loop error in feedback control system. …”
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Conference or Workshop Item -
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Multi-Objective Optimisation of CNC Milling Process for Al 6061 using Modified NSGA-II
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Using Metaheuristics Algorithms (MHAs) to Optimize Water Supply Operation in Reservoirs: a Review
Published 2023“…Decision making; Heuristic algorithms; Optimization; Stochastic systems; Water supply; Complex problems; Decision variables; Meta-heuristics algorithms; Multiple constraint; Nonlinear problems; Optimisations; Variable constraints; Water deficits; Water supply operations; Waters resources; Reservoirs (water)…”
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Multivariable Adaptive Lyapunov Fuzzy Controller for pH Neutralisation Process
Published 2015“…In this study, the nominal neutralisation process condition exhibit nonlinear dynamics and multi-delayed-effects input variables. The proposed controller uses a Takagi-Sugeno fuzzy inference system and it has been optimised by genetic algorithm which minimizing the closed loop error in feedback control system. …”
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Investigating The Performance Of Metaheuristics To Optimize The Revenue Of Semiconductor Supply Chain
Published 2022“…Investigating the performance of metaheuristics to optimise the revenue of the semiconductor supply chain is the final year project that focuses on to identify the supply chain shortage problem related to semiconductors and to compare among the 20 metaheuristics algorithm optimization programmes capable of optimising the semiconductor supply chain. …”
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Monograph -
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Application of optimized higher order sliding mode control on MEMS optical switch
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Conference or Workshop Item -
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Optimisation and performance evaluation of response surface methodology (RSM), artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) in the prediction o...
Published 2023“…Confirmatory experiments were carried out in the biogas plant under this set of optimised variables for a period of two months. The predicted biogas production and methane yield are highly correlated to the actual data with small percentage difference of 1.25 and 5.09 respectively, indicating that ANFIS model was accurate and reliable. …”
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