Search Results - (( simulation optimization method algorithm ) OR ( parameter application use algorithm ))
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1
Optimization of turning parameters using genetic algorithm method
Published 2008“…This method was demonstrated for the optimization of machining parameters for turning operation using conventional lathe machines. …”
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Undergraduates Project Papers -
2
Optimization of milling parameters using ant colony optimization
Published 2008“…The simulation based on ACO algorithm are successful develop and the optimization of parameters values is to maximize the production rate is obtain from the simulation.…”
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Undergraduates Project Papers -
3
An application of simulated Kalman filter optimization algorithm for parameter tuning in proportional-integral-derivative controllers for automatic voltage regulator system
Published 2018“…This paper reports the first attempt to tune gain values in proportional-integral-derivative (PID) controllers using an optimizer called simulated Kalman filter (SKF) algorithm. …”
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Conference or Workshop Item -
4
An application of simulated Kalman filter optimization algorithm for parameter tuning in proportional-integral-derivative controllers for automatic voltage regulator system
Published 2018“…This paper reports the first attempt to tune gain values in proportional-integral-derivative (PID) controllers using an optimizer called simulated Kalman filter (SKF) algorithm. …”
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Conference or Workshop Item -
5
Characterization of PV panel and global optimization of its model parameters using genetic algorithm
Published 2023“…Simulation, optimization and the design of the hybrid systems that include PV are examples of these applications. …”
Article -
6
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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Conference or Workshop Item -
7
Collaborative simulated annealing genetic algorithm for geometric optimization of thermo-electric coolers
Published 2015“…In this chapter, the technical issues of TECs were discussed. After that, a new method of optimizing the dimension of TECs using collaborative simulated annealing genetic algorithm (CSAGA) to maximize the rate of refrigeration (ROR) was proposed. …”
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Book -
8
An Optimized PID Parameters for LFC in Interconnected Power Systems Using MLSL Optimization Algorithm
Published 2016“…In order to enhance the dynamic performance, the optimal parameters of the PID scheme which optimized by the proposed MLSL algorithm are compared with that one’s obtained by GA algorithm. …”
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Article -
9
Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse)
Published 2015“…The results from this experiment show estimated optimal kinetic parameters values, shorter computation time, and better accuracy of simulated results compared with other estimation algorithms.…”
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Article -
10
An Experiment of Ant Algorithms : Case Study of Kota Kinabalu Central Town
Published 2005“…Both algorithms are compared. Simulation is used as a method in this study. …”
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Thesis -
11
1D Multigrid Solver For Finite Element Method
Published 2022“…The new algorithm also has been tested using time simulation. …”
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Monograph -
12
Collaborative simulated annealing genetic algorithm for geometric optimization of thermo-electric coolers
Published 2016“…In this chapter, the technical issues of TECs were discussed. After that, a new method of optimizing the dimension of TECs using collaborative simulated annealing genetic algorithm (CSAGA) to maximize the rate of refrigeration (ROR) was proposed. …”
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Article -
13
Genetic algorithm based method for optimal location placement of flexible ac transmission system devices for voltage profile improvement
Published 2011“…This thesis present a genetic algorithm based method for placement of FACTS devices for voltage profile improvement. …”
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Thesis -
14
Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi
Published 2018“…Simulation results and their comparison with Particle Swarm Optimization based method show high performance and good ability of the proposed method in PMSM parameter estimation.…”
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Article -
15
Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA)
Published 2008“…This paper aims to demonstrate the effectiveness of Multi- Objective Genetic Algorithm Optimization and its robust practical application on the automobile engine valve timing where the variation of performance parameters required for finest tuning to obtain the optimal engine performances. …”
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Proceeding Paper -
16
PID TUNING OF DC MOTOR USING SWARM ITELLIGENCE ALGORITHM
Published 2012“…In this project, Particle Swarm Optimization (PSO) as one of Swarm Intelligence Algorithm based has proposed to be integrated with PID (Proportional, Integral, Derivative) Controller in order to achieve optimal tuning method. …”
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Final Year Project -
17
Optimal power flow using the Jaya algorithm
Published 2016“…Unlike other population-based optimization methods, no algorithm-particular controlling parameters are required for this algorithm. …”
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Article -
18
An Intelligent Voltage Controller for a PV Inverter System Using Simulated Annealing Algorithm-Based PI Tuning Approach
Published 2017“…This study associates an intelligent voltage controller based PI approach for PV electrical inverter by employing a meta-heuristic optimization algorithmic called a Simulated Annealing (SA) algorithm. …”
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Article -
19
A firefly algorithm based hybrid method for structural topology optimization
Published 2020“…Since the direct application of the firefly algorithm cannot generate connected topologies, outputs from the firefly algorithm were used as an initial input material distribution for the OC method. …”
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Article -
20
Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. This FC model uses the root mean squared error as the objective function for optimizing the unknown parameters. …”
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