Search Results - (( parameter optimization based algorithm ) OR ( parameter simulation approach algorithm ))
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1
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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2
A simulation based fly optimisation algorithm for swarms of mini autonomous surface vehicles application
Published 2011“…The optimal simulation parameters can be used for the real application. …”
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3
On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing
Published 2015“…In doing so, this paper reviews two existing parameter free optimization algorithms involving Teaching Learning Based Optimization (TLBO) and Fruitfly Optimization Algorithm (FOA) in an effort to promote their adoption for CIT.…”
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4
A multiobjective simulated Kalman filter optimization algorithm
Published 2018“…SKF is a random based optimization algorithm inspired from Kalman Filter theory. …”
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5
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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6
A Comparison Study Between Two Algorithms Particle Swarm Optimization for Depth Control of Underwater Remotely Operated Vehicle
Published 2013“…This paper investigates two algorithms based on particle swarm optimization (PSO) to obtain optimum parameter. …”
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7
A harmony search-based learning algorithm for epileptic seizure prediction
Published 2016“…Apart from the traditional gradient descent-based approach, metaheuristic algorithms can also be used to determine these parameters. …”
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Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS
Published 2017“…In this paper, heuristic optimization approaches such as genetic algorithm and artificial bee colony are used to optimize the parameters of the antecedent part of interval type-2 fuzzy logic systems. …”
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…These models are developed by integrating multilayer perceptron neural network and evolutionary optimization techniques. Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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10
Simulated Kalman Filter: A Novel Estimation-based Metaheuristic Optimization Algorithm
Published 2016“…In this paper, a new population-based metaheuristic optimization algorithm, named Simulated Kalman Filter (SKF) is introduced. …”
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11
Metaheuristic optimization of perovskite solar cell using hybrid L₃₂ Taguchi DoE-based genetic algorithm
Published 2024“…The proposed approach is realized using Solar Cell Capacitance Simulator (SCAPS-1D) software incorporated with a hybrid L32 Taguchi DoE-based Genetic Algorithm. …”
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…This approach demonstrates the ability of the GOOSE algorithm to simulate complex systems and enhances the robustness and adaptability of the simulation tool by integrating essential behaviours into the computational framework. …”
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An intelligent voltage controller for a PV inverter system using simulated annealing algorithm-based PI tuning approach
Published 2023“…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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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 -
15
Sequence and sequence-less t-way test suite generation strategy based on the elitist flower pollination algorithm
Published 2018“…In line with the emerging field called Search based Software Engineering, many recently developed t-way strategies have adopted meta-heuristic algorithms as the basis of their implementations such as Simulated Annealing, Genetic Algorithm, Ant Colony Optimization Algorithm, Particle Swarm Optimization, Harmony Search and Cuckoo Search, owing their superior performance in term of test size reduction as compared to general computational based strategies, such as General t-way, Test Vector Generator, In Parameter Order General, Jenny, and Automatic Efficient Test Generator. …”
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Thesis -
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Fuzzy adaptive emperor penguin optimizer for global optimization problems
Published 2023“…The Emperor Penguin Optimizer (EPO) is a recently developed population-based metaheuristic algorithm that simulates the huddling behaviour of emperor penguins. …”
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A Kalman Filter Approach for Solving Unimodal Optimization Problems
Published 2015“…In this paper, a new population-based metaheuristic optimization algorithm, named Simulated Kalman Filter (SKF) is introduced. …”
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Metaheuristic Optimization of Perovskite Solar Cell Using Hybrid L32 Taguchi Doe-Based Genetic Algorithm
Published 2025“…The proposed approach is realized using Solar Cell Capacitance Simulator (SCAPS-1D) software incorporated with a hybrid L32 Taguchi DoE-based Genetic Algorithm. …”
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Enhanced genetic algorithm optimization model for a single reservoir operation based on hydropower generation: case study of Mosul reservoir, northern Iraq
Published 2016“…The first algorithm was based on the traditional simulation of reservoir operation, whilst the second algorithm (Salg) enhanced the GAOM by changing the population values of GA through a new simulation process of reservoir operation. …”
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A multi-objective parametric algorithm for sensor-based navigation in uncharted terrains
Published 2023“…Sensor-based motion planning is one the most challenging tasks in robotics where various approaches and algorithms have been proposed to achieve different planning goals. …”
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