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   Articles with "hyperparameter optimization" as a keyword



An automatic hyperparameter optimization DNN model for precipitation prediction

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recommendations! Published in 2021 at "Applied Intelligence"

DOI: 10.1007/s10489-021-02507-y

Abstract: Deep neural networks (DNN) have gained remarkable success on many rainfall predictions tasks in recent years. However, the performance of DNN highly relies upon the hyperparameter setting. In order to design DNNs with the best… read more here.

Keywords: dnn; precipitation; hyperparameter optimization; hyperparameter ... See more keywords

Scalable Gaussian process-based transfer surrogates for hyperparameter optimization

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recommendations! Published in 2017 at "Machine Learning"

DOI: 10.1007/s10994-017-5684-y

Abstract: Algorithm selection as well as hyperparameter optimization are tedious task that have to be dealt with when applying machine learning to real-world problems. Sequential model-based optimization (SMBO), based on so-called “surrogate models”, has been employed… read more here.

Keywords: surrogate; model; optimization; transfer ... See more keywords

WACSO: Wolf Crow Search Optimizer for Convolutional Neural Network Hyperparameter Optimization

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recommendations! Published in 2025 at "Neural Processing Letters"

DOI: 10.1007/s11063-025-11740-2

Abstract: Convolutional Neural Networks (CNNs) experience performance and training efficiency changes according to the selection of correct hyperparameters. The research presents WACSO which combines Crow Search Optimization with Grey Wolf Optimizer to improve Convolutional Neural Networks… read more here.

Keywords: hyperparameter optimization; convolutional neural; wacso; crow search ... See more keywords

Comparative Analysis of Automated Machine Learning for Hyperparameter Optimization and Explainable Artificial Intelligence Models

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recommendations! Published in 2025 at "IEEE Access"

DOI: 10.1109/access.2025.3566427

Abstract: Artificial intelligence (AI) has been increasingly applied to solve complex real-world problems. One of the most significant challenges in AI lies in selecting and fine-tuning the optimal algorithm for a given task. Automated Machine Learning… read more here.

Keywords: hyperparameter optimization; artificial intelligence; analysis; machine learning ... See more keywords

Deep Learning Algorithms and Parallel Distributed Computing Techniques for High-Resolution Load Forecasting Applying Hyperparameter Optimization

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recommendations! Published in 2022 at "IEEE Systems Journal"

DOI: 10.1109/jsyst.2021.3130080

Abstract: Electrical load forecasting is one of the critical tasks that helps power utility companies in planning and operation as well as the energy managementsystem (EMS) in controlling and optimizing the power grid’s performance. It guarantees… read more here.

Keywords: learning algorithms; hyperparameter optimization; load forecasting; parallel distributed ... See more keywords

Hyperparameter Optimization Method for Affine Projection Algorithm Based on Deep Unrolling

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recommendations! Published in 2025 at "IEEE Signal Processing Letters"

DOI: 10.1109/lsp.2025.3639373

Abstract: In this letter, we propose a hyperparameter optimization method for adaptive filtering based on deep unrolling, termed the deep unrolling affine projection (DAP) algorithm. The core idea is to reformulate the iterative structure of the… read more here.

Keywords: hyperparameter optimization; based deep; affine projection; deep unrolling ... See more keywords
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Dynamical Hyperparameter Optimization via Deep Reinforcement Learning in Tracking

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recommendations! Published in 2021 at "IEEE Transactions on Pattern Analysis and Machine Intelligence"

DOI: 10.1109/tpami.2019.2956703

Abstract: Hyperparameters are numerical pre-sets whose values are assigned prior to the commencement of a learning process. Selecting appropriate hyperparameters is often critical for achieving satisfactory performance in many vision problems, such as deep learning-based visual… read more here.

Keywords: optimization via; hyperparameter optimization; dynamical hyperparameter; hyperparameter ... See more keywords

Impact of Healthcare on Stock Market Volatility and Its Predictive Solution Using Improved Neural Network

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recommendations! Published in 2022 at "Computational Intelligence and Neuroscience"

DOI: 10.1155/2022/7097044

Abstract: The unprecedented Corona Virus Disease (COVID-19) pandemic has put the world in peril and shifted global landscape in unanticipated ways. The SARSCoV2 virus, which caused the COVID-19 outbreak, first appeared in Wuhan, Hubei Province, China,… read more here.

Keywords: neural network; stock market; hyperparameter optimization; volatility ... See more keywords

An Intelligent and Reliable Hyperparameter Optimization Machine Learning Model for Early Heart Disease Assessment Using Imperative Risk Attributes

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recommendations! Published in 2022 at "Journal of Healthcare Engineering"

DOI: 10.1155/2022/9882288

Abstract: Heart disease is a severe disorder, which inflicts an adverse burden on all societies and leads to prolonged suffering and disability. We developed a risk evaluation model based on visible low-cost significant noninvasive attributes using… read more here.

Keywords: hyperparameter optimization; optimization machine; risk; heart disease ... See more keywords

Convolution neural network hyperparameter optimization using modified particle swarm optimization

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recommendations! Published in 2024 at "Bulletin of Electrical Engineering and Informatics"

DOI: 10.11591/eei.v13i2.6112

Abstract: Based on the literature review, a convolutional neural network (CNN) is one of the deep learning techniques most often used for classification problems, especially image classification. Various approaches have been proposed to improve accuracy performance.… read more here.

Keywords: hyperparameter optimization; particle swarm; pso; neural network ... See more keywords

Multi-layer perceptron hyperparameter optimization using Jaya algorithm for disease classification

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recommendations! Published in 2024 at "Indonesian Journal of Electrical Engineering and Computer Science"

DOI: 10.11591/ijeecs.v35.i1.pp620-630

Abstract: This study introduces an innovative hyperparameter optimization approach for enhancing multilayer perceptrons (MLP) using the Jaya algorithm. Addressing the crucial role of hyperparameter tuning in MLP’s performance, the Jaya algorithm, inspired by social behavior, emerges… read more here.

Keywords: hyperparameter optimization; hyperparameter; using jaya; jaya algorithm ... See more keywords