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Parametric modelling of a TRMS using dynamic spread factor particle swarm optimisation
Published 2009“…Particle swarm optimization (PSO) is demonstrated as an efficient global search method for nonlinear complex systems without any a priory knowledge of the system structure. …”
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Proceeding Paper -
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Determining optimal transportation allocation using linear programming methods / Tengku Mohd Hazimi Tuan Hassan and Maslin Masrom
Published 2022“…The efficiency and effectiveness of the transportation problem algorithm are determined using the Excel Solver. The excel solution and sensitivity analysis provide information about the optimal distribution strategy for their products. …”
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Article -
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Gravitational energy harvesting system based on multistage braking technique for multilevel elevated car parking building
Published 2020“…Thirdly, modeling of electrical and mechanical parameters for the presented system such that the system performance matching the model, this process is performed by using a parameter optimization algorithm. …”
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Thesis -
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Voting algorithms for large scale fault-tolerant systems
Published 2011“…In a nut shell, we tried to introduce voting algorithms and structures suitable for large scale fault-tolerant systems which have optimal and proper time complexity (in parallel voting algorithms) and more reliability and availability (in enhanced m-out-of-n voting algorithm) compared to the basic types.…”
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Thesis -
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Particle swarm optimization (PSO) for CNC route problem
Published 2002“…The algorithm used in this project is the Global Best (gbest) algorithm where it is a basic algorithm of Particle Swarm Optimization which applicable the shortest time and path of CNC machine to complete the process of drilling. …”
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Undergraduates Project Papers -
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Algorithm development for optimization of a refrigeration system
Published 2010“…This thesis deals with algorithm development for optimization of a refrigeration system. …”
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Undergraduates Project Papers -
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Optimal power flow based on fuzzy linear programming and modified Jaya algorithms
Published 2017“…Meanwhile, the proposed QOJaya algorithm produces better results than the basic Jaya method in terms of solution optimality and convergence speed. …”
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Thesis -
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Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System
Published 2019“…In this paper, the particle swan optimization algorithm (PSO) was used to obtain an optimal set of initial parameters for Reduce Kernel FLN (RK-FLN), thus, creating an optimal RKFLN classifier named PSO-RKELM. …”
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Conference or Workshop Item -
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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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Thesis -
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A hybrid algorithm based on artificial bee colony and artificial rabbits optimization for solving economic dispatch problem
Published 2023“…This algorithm synergizes the ABC algorithm and Artificial Rabbits Optimization (ARO) algorithm. …”
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Conference or Workshop Item -
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Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection
Published 2022“…The first modification enhances the initial population of the MBGWO using a heuristic based Ant Colony Optimisation algorithm. …”
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Thesis -
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Modelling and optimisation of oil palm trunk core biodelignification using neural network and genetic algorithm
Published 2019“…These models were used to find the optimised the network output using genetic algorithm search. …”
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Conference or Workshop Item -
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Optimization Of Pid Controller Using Grey Wolf Optimzer And Dragonfly Algorithm
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Monograph -
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Optimisation of Surface Roughness in 3D Printing Using the Bees Algorithm
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Book Chapter -
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Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems
Published 2022“…The performance of the fuzzy adaptive teaching learning-based optimization is evaluated against other metaheuristic algorithms including basic teaching learning-based optimization on 23 unconstrained global test functions. …”
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