Search Results - (( data optimization means algorithm ) OR ( parameter optimization based algorithm ))
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Individual-tree segmentation and extraction based on LiDAR point cloud data
Published 2024“…Nonetheless, the optimal parameter settings for the watershed algorithm need to be adjusted based on stand density. …”
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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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VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern
Published 2012“…GA is a widely used optimization algorithm based on the concept of survival of the fittest. …”
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Stock price predictive analysis: An application of hybrid barnacles mating optimizer with artificial neural network
Published 2023“…As a relatively new optimization algorithm, it has been shown to be effective in addressing various optimization problems. …”
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Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin
Published 2014“…Bat algorithm was employed to optimize the training parameters such as learning rate, momentum rate and number of neurons in hidden layers. …”
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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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Hybrid bat algorithm hybrid-artificial neural network for modeling operating photovoltaic module temperature / Noor Rasyidah Hussin
Published 2014“…Bat algorithm was employed to optimize the training parameters such as learning rate, momentum rate and number of neurons in hidden layers. …”
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Stock price predictive analysis : An application of hybrid barnacles mating optimizer with artificial neural network
Published 2023“…As a relatively new optimization algorithm, it has been shown to be effective in addressing various optimization problems. …”
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Analysis of toothbrush rig parameter estimation using different model orders in Real-Coded Genetic Algorithm (RCGA)
Published 2018“…Realcoded genetic algorithm (RCGA) as a stochastic global search method was applied for optimization. …”
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Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…Hybridizing the Deep Neural Network (DNN) with the K-Means Clustering algorithm will increase the accuracy and reduce the data complexity of the Lorenz dataset. …”
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Rice Predictive Analysis Mechanism Utilizing Grey Wolf Optimizer-Least Squares Support Vector Machines
Published 2015“…In this regard, this study proposes a hybridization of LSSVM with a new Swarm Intelligence (SI) algorithm namely, Grey Wolf Optimizer (GWO). With such hybridization, the hyper-parameters of interest are automatically optimized by the GWO. …”
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Identification of continuous-time hammerstein model using improved archimedes optimization algorithm
Published 2024“…Therefore, this article identified various continuous-time Hammerstein models based on an improved Archimedes optimization algorithm (IAOA) to address these concerns. …”
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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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Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…his thesis implements a novel nature-inspired metaheuristic optimization algorithm, namely the modified Multi-Verse Optimizer (mMVO) algorithm, to identify the continuous-time model of Hammerstein system. …”
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Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems
Published 2019“…Hence, a memory-based optimization tool has good potential to retain the optimal design parameter during the PID tuning process. …”
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Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems
Published 2019“…Hence, a memory-based optimization tool has good potential to retain the optimal design parameter during the PID tuning process. …”
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Predicting longitudinal dispersion coefficient using ensemble models and optimized multi-layer perceptron models
Published 2024“…The honey badger optimization algorithm (HBOA), salp swarm algorithm (SASA), firefly algorithm (FIFA), and particle swarm optimization algorithm (PASOA) are used to adjust the MULP parameters. …”
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