Результаты поиска - "Bayesian optimization algorithm"
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Research on Cultivated Land Quality Assessment at the Farm Scale for Black Soil Region in Northeast China Based on Typical Period Remote Sensing Images from Landsat 9
Опубликовано 2025-06-01Предметы: Полный текстRapid and efficient evaluation of cultivated land quality in black soil regions at the farm scale using remote sensing techniques is crucial for resource protection. However, current studies face challenges in developing convenient and reliable models that directly leverage raw spectral reflectance....
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Artificial intelligence-based Bayesian optimization and transformer model for tennis motion recognition
Опубликовано 2025-06-01“...Then, the optimal pruning rate of each layer of the network is found by using Bayesian optimization algorithm to improve the efficiency and accuracy of subnet search. ...”Because the traditional methods are used to analyze human motion behavior, there are large errors and serious over-fitting phenomenon, so a novel tennis motion recognition based on Bayesian optimization and transformer model is proposed in this paper. First, we use an improved generative adversarial...
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Novel Conformable Fractional Order Unbiased Kernel Regularized Nonhomogeneous Grey Model and Its Applications in Energy Prediction
Опубликовано 2025-07-01“...The parameter estimation of the CFUKRNGM model requires solving a linear equation with a lower order than the KRNGM model, and is automatically calibrated through the Bayesian optimization algorithm. Experimental results show that the CFUKRNGM model achieves superior prediction accuracy and greater generalization performance compared to both the KRNGM and traditional grey models....”Grey models have attracted considerable attention as a time series forecasting tool in recent years. Nevertheless, the linear characteristics of the differential equations on which traditional grey models rely frequently result in inadequate predictive accuracy and applicability when addressing intr...
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A novel method for distracted driving behaviors recognition with hybrid CNN-BiLSTM-AM model
Опубликовано 2025-06-01“...A fully connected neural network layer is applied to establish a nonlinear mapping relationship between the extracted features and driving behavior categories. Bayesian optimization algorithm is adopted to automatically optimize hyperparameters of the network so as to improve training efficiency and performance of the proposed model. ...”Abstract A novel deep learning framework for recognition of distracted driving behavior is proposed in this paper. The proposed framework consists of hybrid convolutional neural network and bidirectional long short term memory network to extract multi-scale spatiotemporal features of high-dimensiona...
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IT Diagnostics of Parkinson’s Disease Based on the Analysis of Voice Markers and Machine Learning
Опубликовано 2023-06-01“...The model was trained using the Knn and Random Forest algorithms, as well as the Bayesian neural network. The Bayesian optimization algorithm and the GridSearch method were used to find the best model hyperparameters. ...”The results of studying the parameters of the spectra of speech signals by machine learning with the use of neural networks are presented. This study was carried out in order to confirm experimentally the possibility of performing an assessment of these parameters for the detection of Parkinson’s di...
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A general two-group constants estimator for 17x17 PWR assembly configurations using artificial neural networks
Опубликовано 2025-06-01“...The number of layers and hyperparameters used in the ANN has been determined using the KerasTuner optimization framework employing the Bayesian optimization algorithm. Serpent code has been used to generate two-group constants for random assembly configurations to obtain training and test data. ...”In this study, a preliminary general two-group constants predictor using artificial neural networks (ANNs) for pressurized water reactor (PWR) based assembly designs is established. Users can input arbitrary assembly specifications to the trained ANN, enabling the instant generation of group constan...
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Surface water quality prediction based on BOA-BiLSTM model(基于BOA-BiLSTM模型的地表水水质预测)
Опубликовано 2025-05-01“...∶为准确评估监测条件有限的平原河网小流域河水水质演变趋势，预知水质变化情况，利用浙江省台州市南官河2021年6月至2023年6月的水质监测数据，基于贝叶斯优化算法（Bayesian optimization algorithm，BOA）和双向长短期记忆神经网络（bi-directional long short-term memory，BiLSTM）建立了地表水水质预测模型。...”∶To accurately assess the water quality evolution trend of small watersheds in plain river networks with limited monitoring conditions and predict the change of water quality in advance, based on the water quality monitoring data of Nanguan River in Taizhou, Zhejiang province from June 2021 to June...
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Bayesian optimization of underground railway tunnels using a surrogate model
Опубликовано 2025-01-01“...The results demonstrate that the proposed optimization framework, which combines the Bayesian optimization algorithm with surrogate models, effectively explores trade-offs among multiple design parameters. ...”The assessment of soil–structure interaction (SSI) under dynamic loading conditions remains a challenging task due to the complexities of modeling this system and the interplay of SSI effects, which is also characterized by uncertainties across varying loading scenarios. This field of research encom...
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An echo state network based on enhanced intersecting cortical model for discrete chaotic system prediction
Опубликовано 2025-07-01“...The model incorporates a neuron model with internal dynamics, including adaptive thresholds and inter-neuron feedback, into the reservoir structure. A Bayesian Optimization algorithm was employed for the selection of hyperparameters. ...”IntroductionThe prediction of chaotic time series is a persistent problem in various scientific domains due to system characteristics such as sensitivity to initial conditions and nonlinear dynamics. Deep learning models, while effective, are associated with high computational costs and large data r...
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Satellite-Derived Bathymetry Combined With Sentinel-2 and ICESat-2 Datasets Using Deep Learning
Опубликовано 2025-01-01“...This article proposes a convolutional neural network and bidirectional long short-term memory hybrid model based on the Bayesian optimization algorithm (BOA-CNN-BILSTM) to enhance bathymetric inversion accuracy and efficiency. ...”Accurate bathymetric data are critical for marine ecological balance and resource management. Deep learning algorithms, known for their capacity to model complex, multivariate, and nonlinear relationships, have been increasingly applied to satellite-derived bathymetry. However, existing deep learnin...
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Hyperparameter tuned deep learning-driven medical image analysis for intracranial hemorrhage detection.
Опубликовано 2025-01-01“...Lastly, the Bayesian optimizer algorithm (BOA) is implemented for the hyperparameter selection of the DL technique. ...”Intracranial haemorrhage (ICH) is a crucial medical emergency that entails prompt assessment and management. Compared to conventional clinical tests, the need for computerized medical assistance for properly recognizing brain haemorrhage from computer tomography (CT) scans is more mandatory. Various...
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