Search Results - (( evolution simulation model algorithm ) OR ( variable optimization method algorithm ))
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Model predictive control based on Lyapunov function and near state vector selection of four-leg inverter / Abdul Mannan Dadu
Published 2018“…This dissertation has focused on Lyapunov model predictive control (L-MPC) methods, in which Lyapunov control law is employed in the cost function to minimize the error between the desired control variables and the actual control variables of a three-phase four-leg inverter to optimize closed-loop system performance. …”
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Two level Differential Evolution algorithms for ARMA parameters estimatio
Published 2013“…The performance of the algorithm is evaluated using both simulated ARMA models and practical rotary motion system. …”
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Proceeding Paper -
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Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse)
Published 2015“…Global optimisation method includes differential evolution algorithm, which will be used in this research. …”
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Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization
Published 2014“…Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. …”
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Optimization of handover algorithms in 3GPP long term evolution system
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Proceeding Paper -
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Optimization of PID Parameters Utilizing Variable Weight Grey-Taguchi Method and Particle Swarm Optimization
Published 2017“…Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. …”
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Optimization Of Bar Linkage By Using Genetic Algorithms
Published 2005“…This thesis presents the method of using simple Genetic Algorithms (GAs) in optimizing the size of bar linkage with discrete design variables and continues design variables. …”
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Monograph -
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Optimizing the placement of fire department in Kulim using greedy heuristic and simplex method / Muhammad Abu Syah Mohd Suzaly
Published 2023“…The first method is greedy heuristic method. Greedy heuristics is a type of optimization algorithm that makes decisions based on locally optimal solutions. …”
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Thesis -
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Evolution of RF-signal cognition for wheeled mobile robots using pareto multi-objective optimization
Published 2009“…This article describes a simulation model in which a multi-objective approach is utilized for evolving an artificial neural networks (ANNs) controller for an autonomous mobile robot. …”
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Mine blast algorithm for optimization of truss structures with discrete variables
Published 2012“…In this study a novel optimization method is presented, the so called mine blast algorithm (MBA). …”
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Autotuning PID Controllers for Quadplane Hybrid UAV using Differential Evolution Algorithm
Published 2024“…The unified RBF model is then used for autotuning the PID controller using the DE algorithm. …”
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An FPGA implementation of exp-bet scheduling algorithm in LTE networks / Yusmardiah Yusuf
Published 2017“…The design using Simulink and System generator can greatly reduce the process cycle from the algorithm to hardware. The metric equation of the EXP-BET algorithm is modelled and simulated using the MATLAB Simulink environment and System Generator tool provided by Xilinx. …”
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A firefly algorithm based hybrid method for structural topology optimization
Published 2020“…In this paper, a firefly algorithm based hybrid algorithm through retaining global convergence of firefly algorithm and ability to generate connected topologies of optimality criteria (OC) method is proposed as an alternative method to solve stress-based topology optimization problems. …”
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Autotuning PID Controllers for Quadplane Hybrid UAV using Differential Evolution Algorithm
Published 2024“…The unified RBF model is then used for autotuning the PID controller using the DE algorithm. …”
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A MODIFIED PARTICLE SWARM OPTIMIZATION ALGORITHM FOR WELLBORE TRAJECTORY DESIGN
Published 2021“…To address this issue, a new hybridization of cellular automata (CA) technique with grey wolf optimization (GWO) and particle swarm optimization (PSO) algorithms is proposed in this work which solves these three optimization objectives of drilling through 17 tuning variables. …”
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