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method algorithm » mould algorithm (Expand Search)
data detection » data injection (Expand Search)
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Unlocking new frontiers in epilepsy through AI: From seizure prediction to personalized medicine
Published 2025“…Ethical considerations, such as safeguarding patient privacy, ensuring data security, and mitigating algorithmic bias, underscore the importance of responsible AI integration. …”
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An Effective Hybrid NARX-LSTM Model for Point and Interval PV Power Forecasting
Published 2021“…Then, the stacked LSTM model, optimized by Tabu search algorithm, uses the residual error correction associated with the original data to produce a point and interval PVPF. …”
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367
Integrated Energy Optimization and Stability Control Using Deep Reinforcement Learning for an All-Wheel-Drive Electric Vehicle
Published 2025“…To this end, three model-free DRL-based methods, based on deep deterministic policy gradient (DDPG), twin delayed deep deterministic policy gradient (TD3), and TD3 enhanced with curriculum learning (CL TD3), are developed for determining optimal yaw moment control and energy optimization online. …”
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368
Spectral energy balancing system with massive MIMO based hybrid beam forming for wireless 6G communication using dual deep learning model
Published 2024“…<p>This work aims to provide an effective hybrid beam forming method with Dual-Deep-Network to overcome overhead for mm-wave massive MIMO systems. …”
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369
Wide area monitoring system operations in modern power grids: A median regression function-based state estimation approach towards cyber attacks
Published 2023“…The algorithm was stationed at each monitoring node using interacting multiple model (IMM)-based fusion architecture. …”
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370
Automated Deep Learning BLACK-BOX Attack for Multimedia P-BOX Security Assessment
Published 2022“…<p>Resistance to differential cryptanalysis is a fundamental security requirement for symmetric block ciphers, and recently, deep learning has attracted the interest of cryptography experts, particularly in the field of block cipher cryptanalysis, where the bulk of these studies are differential distinguisher based black-box attacks. This paper provides a deep learning-based decryptor for investigating the permutation primitives used in multimedia block cipher encryption algorithms.We aim to investigate how deep learning can be used to improve on previous classical works by employing ciphertext pair aspects to maximize information extraction with low-data constraints by using convolution neural network features to discover the correlation among permutable atoms to extract the plaintext from the ciphered text without any P-box expertise. …”
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371
Automatic and Intelligent Stressor Identification Based on Photoplethysmography Analysis
Published 2021“…In particular, this study proposes a novel algorithm that first detects instances of stress and then classifies the stressor type using photoplethysmography (PPG) data from wearable smartwatches. …”
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Wearable wrist to finger photoplethysmogram translation through restoration using super operational neural networks based 1D-CycleGAN for enhancing cardiovascular monitoring
Published 2024“…Current signal processing techniques, and even state-of-the-art machine learning algorithms, frequently struggle to effectively restore the inherent bodily signals amidst the array of randomly generated distortions. …”
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373
Various Faults Classification of Industrial Application of Induction Motors Using Supervised Machine Learning: A Comprehensive Review
Published 2025“…Machine learning algorithms are a set of data-driven rules that are able to classify specific faults in induction motors, which will be explained further in this review paper. …”
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374
Navigating the Landscape of Deep Reinforcement Learning for Power System Stability Control: A Review
Published 2023“…<p dir="ltr">The widespread penetration of inverter-based resources has profoundly impacted the electrical stability of power systems (PSs). …”
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375
An Adaptive Sliding Mode Control for a Dual Active Bridge Converter With Extended Phase Shift Modulation
Published 2023“…The conventional single-phase shift (SPS) modulation-based DAB converter is known to be inefficient. Hence, an optimization algorithm based on the Lagrange multiplier method (LMM) is proposed to minimize both backflow power and inductor current stress simultaneously. …”
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The Role of Machine Learning in Diagnosing Bipolar Disorder: Scoping Review
Published 2021“…We identified different machine learning models used in the selected studies, including classification models (18, 55%), regression models (5, 16%), model-based clustering methods (2, 6%), natural language processing (1, 3%), clustering algorithms (1, 3%), and deep learning–based models (3, 9%). …”
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378
Artificial Intelligence for Cochlear Implants: Review of Strategies, Challenges, and Perspectives
Published 2024“…The process involves receiving the speech signal in analog form, followed by various signal processing algorithms to make it compatible with devices of limited capacities, such as cochlear implants (CIs). …”
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379
A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI
Published 2025“…After handling missing values, balancing the dataset, and analyzing the classifier’s performance, it is found that tree-based algorithms, particularly RF, perform better for all the datasets. …”
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380