Search Results - (( basic simulation model algorithm ) OR ( parameter optimization method algorithm ))
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Genetic algorithm based method for optimal location placement of flexible ac transmission system devices for voltage profile improvement
Published 2011“…The IEEE 14-bus, 57-bus and 118-bus test systems are utilized during this research to verify the recommended method. The modeling of power systems, FACTS devices and genetic algorithms are performed through MATLAB/PSAT simulation. …”
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Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller
Published 2010“…It is observed that the APFLC showed convincing performance over the entire simulation of the Pico-satellite. Genetic Algorithm (GA) is a computational model inspired by evaluation. …”
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INTELLIGENT OPTIMIZATION OF INTERLINE POWER FLOW CONTROLLER IN TRANSMISSION SYSTEM
Published 2010“…The optimal parameters are derived to minimize the transmission line losses using three intelligent optimization techniques, namely Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Simulated Annealing (SA). …”
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Intelligently tuned weights based robust H∞ controller design for pneumatic servo actuator system with parametric uncertainty
Published 2011“…The PSO algorithm is used to minimize the infinity norm of the transfer functions matrix of the nominal closed loop system to obtain the optimal parameters of the weighting function. …”
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Tree physiology optimization on SISO and MIMO PID control tuning
Published 2018“…This concept may improve the search mechanism with a better trade-off between diversification and intensification search. A simulation of SISO control system and an industrial application of MIMO control are applied to demonstrate the effectiveness of the proposed algorithm and compared with other optimization methods such as particle swarm optimization, Zieglerâ��Nichols, Tyreusâ��Luyben and Chienâ��Hronesâ��Reswick methods. …”
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Tree physiology optimization on SISO and MIMO PID control tuning
Published 2018“…This concept may improve the search mechanism with a better trade-off between diversification and intensification search. A simulation of SISO control system and an industrial application of MIMO control are applied to demonstrate the effectiveness of the proposed algorithm and compared with other optimization methods such as particle swarm optimization, Zieglerâ��Nichols, Tyreusâ��Luyben and Chienâ��Hronesâ��Reswick methods. …”
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Reproducing kernel Hilbert space method for cox proportional hazard model
Published 2016“…This algorithm is used to determine the vector i a that enables us to find the optimal parameters of ƒ(x)which is simplified as F(x)= ∑aᵢK(x,xᵢ) . …”
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Evaluation method of rationality of urban landscape facility design based on neural network
Published 2025“…Specifically, our work encompasses the following key aspects: 1) Introducing the relevant theoretical knowledge and research progress in urban landscape facility design. 2) Elucidating the basic principles and structures of the backpropagation neural network (BPNN), along with the proposal of an improved genetic algorithm-back propagation neural network (GA-BP) to address the limitations of BPNN. 3) Conducting experiments to determine the optimal parameters for the GA-BP model once training is finished. …”
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Power Delivery Network Modeling And Simulation By Using Delaunay-Voronoi Triangulation And The Latency Insertion Method
Published 2018“…The research is focused into the analysis of PDN by modeling and simulation of the power plane. In the project, power plane is modeled using Delaunay-Voronoi algorithm and for simulation, a fast transient simulation algorithm which is latency insertion method (LIM) is applied. …”
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Optimization of turning parameters using genetic algorithm method
Published 2008“…This study about development of optimization for turning parameters based on the Genetic Algorithm (GA). …”
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Parameters optimization of surface grinding process with particles swarm optimization, gravitational search, and sine cosine algorithms: a comparative analysis
Published 2018“…The efficiency of the three algorithms are evaluated and compared with previous results obtained by other optimization methods on similar studies. …”
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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 turning parameters using ant colony optimization
Published 2008“…The project objectives are to develop Ant Colony Optimization (ACO) algorithm for CNC turning process and to optimize turning parameters for minimized production cost per unit. …”
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Parameter estimation in double exponential smoothing using genetic algorithm / Foo Fong Yeng, Lau Gee Choon and Zuhaimy Ismail
Published 2014“…Trial and error often serves as the best method to determine the parameter. Therefore, a good optimization technique is required for identify the best parameter in minimizing the forecast errors. …”
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Research Reports -
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Fitness-guided particle swarm optimization with adaptive Newton-Raphson for photovoltaic model parameter estimation
Published 2025Subjects:Article -
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Application Of Genetic Algorithms For Robust Parameter Optimization
Published 2010“…Genetic algorithms (GA) are fairly recent in this respect but afford a novel method of parameter optimization. …”
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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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Inversion of 2D and 3D DC resistivity imaging data for high contrast geophysical regions using artificial neural networks / Ahmad Neyamadpour
Published 2010“…In order to study the numerical simulation of the measured data for a given subsurface parameter, the basis of the finite difference method and the various boundary conditions are explained here. …”
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Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study
Published 2023“…—Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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