过去一年中添加的文章，按日期排序

A data-driven ANN model for estimation of melt-pool characteristics in SLM process

D Bombe, A Agrawal, R Kumar - 2024 - dspace.iitrpr.ac.in
5 天前 - … layered to manufacture a near-net-shaped metallic 3D component. The SLM process
involves multiple physical … model by considering various physical phenomena of the SLM …
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A Data-Physical Fusion Method for Economic Dispatch Considering High Renewable Penetration and Security Constraints

Y Dai, W Xu, X Wu, M Yan, F Xue, J Zhao - Available at SSRN 4873714 - papers.ssrn.com
5 天前 - … Then, a physics-informed neural network based on the deep deterministic policy
gradient (DDPG) algorithm is employed for fine-tuning and transfer learning. Physical models …
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A novel domain adaptation method with physical constraints for shale gas production forecasting

L Gou, Z Yang, C Min, D Yi, X Li, B Kong - Applied Energy, 2024 - Elsevier
5 天前 - … from shale gas production as physical constraints, enhancing the interpretability
and accuracy of the deep learning model. The main contributions of this article are as follows: …
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[PDF] ieee.org

Physical Layer Spoof Detection and Authentication for IoT Devices using Deep Learning Methods

D Huang, A Al-Hourani - … Transactions on Machine Learning in …, 2024 - ieeexplore.ieee.org
6 天前 - … Unlike other physical layer approaches such as physical unclonable functions (PUF)
[6], RFF does not require any hardware or software modifications during or after manufac…
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Intelligent deep model based on convolutional neural network's and multi-layer perceptron to classify cardiac abnormality in diabetic patients

M Saraswat, AK Wadhwani, S Wadhwani - Physical and Engineering …, 2024 - Springer
7 天前 - … However, this paper explores the application of machine learning algorithms and
deep learning algorithm to autonomously identify cardiac diseases in diabetic patients in the …
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Prediction and decision support of soil pollution remediation effect in mines based on neural network method

X Yue, L Fei, Y Sun, S Zhu, A Li - … International Symposium on …, 2024 - spiedigitallibrary.org
7 天前 - … This article aims to construct a prediction model based on neural networks, using
deep learning technology to efficiently analyze and mine multivariate data including various …
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Intellectual Assessment of Amyotrophic Lateral Sclerosis Using Deep Resemble Forward Neural Network

A Alqahtani, S Alsubai, M Sha, AK Dutta, YD Zhang - Neural Networks, 2024 - Elsevier
7 天前 - ALS (Amyotrophic Lateral Sclerosis) is a neurodegenerative disorder causing
profound physical disability that severely impairs a patient's life expectancy and quality of life. It …
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Optimization by a genetic algorithm of nanopyramidal broadband quasi-perfect absorbers with deeper insight into the stability of optimal solutions

A Mayer, O Deparis, M Lobet - Machine Learning in Photonics, 2024 - spiedigitallibrary.org
8 天前 - … Machine Learning has become a trendy paradigm in the physical sciences. Deep
Learning in particular has given rise to impressive results in image recognition, language …
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Deep Reinforcement Learning Based Uplink Security Enhancement for STAR-RIS-Assisted NOMA Systems With Dual Eavesdroppers

X Qin, Z Song, J Wang, S Du, J Gao… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
9 天前 - … physical layer security (PLS) [14]. However, it is important to mention that when the
RIS is employed to enhance the PLS, the vision is to simultaneously improve the legitimate …
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Priority-Based Load Balancing With Multi-Agent Deep Reinforcement Learning for Space-Air-Ground Integrated Network Slicing

H Tu, P Bellavista, L Zhao, G Zheng… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
9 天前 - … In order to solve the MOOP, we propose a novel two-layer multi-agent deep
deterministic policy gradient (MADDPG) algorithm. With the above background, the main …
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