Search Results - (( parameter optimization means algorithm ) OR ( parameter evaluations _ algorithm ))
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Impact of evolutionary algorithm on optimization of nonconventional machining process parameters
Published 2025“…Using a Python environment, three evolutionary algorithms such as, Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Firefly Algorithm (FA), were simulated to evaluate their effectiveness in minimizing surface roughness (Ra). …”
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A Hybrid Least Squares Support Vector Machine with Bat and Cuckoo Search Algorithms for Time Series Forecasting
Published 2020“…However, its operation relies on two important parameters (regularization and kernel). Pre-determining the values of parameters will affect the results of the forecasting model; hence, to find the optimal value of these parameters, this study investigates the adaptation of Bat and Cuckoo Search algorithms to optimize LSSVM parameters. …”
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Bouc-Wen hysteresis parameter optimization for magnetorheological damper using Cuckoo search algorithm
Published 2020“…Cuckoo search algorithm is used to optimize the parameters in phenomenological Bouc-Wen model. …”
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Efficient Time-Varying q-Parameter Design for q-Incremental Least Mean Square Algorithm with Noisy Links
Published 2022“…Finally, extensive simulations have been done to evaluate the performance of the proposed algorithm for various choices of optimal q-values. …”
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Analysis of toothbrush rig parameter estimation using different model orders in Real-Coded Genetic Algorithm (RCGA)
Published 2018“…The influence of conventional genetic algorithm parameter - generation gap has been investigated too. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. Then, the developed algorithm is implemented to estimate the parameters of the Lorenz system. …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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Stock price predictive analysis: An application of hybrid barnacles mating optimizer with artificial neural network
Published 2023“…In this study, the Barnacles Mating Optimizer (BMO) is employed as an optimization tool to automatically optimize these parameters. …”
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Optimization of modified Bouc–Wen model for magnetorheological damper using modified cuckoo search algorithm
Published 2021“…An engineering optimization application was chosen to evaluate the performance of the algorithm in complex engineering applications. …”
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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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Stock price predictive analysis : An application of hybrid barnacles mating optimizer with artificial neural network
Published 2023“…In this study, the Barnacles Mating Optimizer (BMO) is employed as an optimization tool to automatically optimize these parameters. …”
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Analysis of Toothbrush Rig Parameter Estimation Using Different Model Orders in Real Coded Genetic Algorithm (RCGA)
Published 2024“…The influence of conventional genetic algorithm parameter - generation gap has been investigated too. …”
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Application and evaluation of the evolutionary algorithms combined with conventional neural network to determine the building energy consumption of the residential sector
Published 2025“…The primary objectives were to assess the performance of three evolutionary algorithms ? Heap-Based Optimizer (HBO), Multiverse Optimizer (MVO), and Whale Optimization Algorithm (WOA) ? …”
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Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems
Published 2023“…Stochastic gradient descent (SGD) is one of the most common algorithms used in solving large unconstrained optimization problems. …”
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A Hybrid Neural Network-Based Improved PSO Algorithm for Gas Turbine Emissions Prediction
Published 2025“…Overall, the hybrid model achieves high prediction accuracy, particularly with optimized PSO parameter selection using seed random generators. ? …”
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Optimization Of Pid Controller For Double-Link Flexible Robotic Manipulator Using Metaheuristic Algorithms
Published 2019“…This signifies that, the PSO and ABC algorithm are very effective in optimizing the PID parameters.…”
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Proceeding -
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Feature optimization with metaheuristics for Artificial Neural Network-based chiller power prediction
Published 2025“…The algorithm identified seven optimal features primarily comprising temperature and humidity parameters. …”
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A multi-objective parametric algorithm for sensor-based navigation in uncharted terrains
Published 2023“…In this paper, a novel parametric algorithm is proposed that is able to handle different planning goals by means of a set of objective-controller parameters. …”
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Improved flower pollination optimization algorithm based on swap operator and dynamic switch probability selection
Published 2023“…The proposed algorithm is ranked first among the stated algorithms with respect to its performance in getting the optimal solution…”
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