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Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval
Published 2024“…Generally, RKPCA reduces the number of samples in the training data set and then builds the KPCA model based on this data set. In this paper, the proposed algorithm selects relevant observations from the original data set by utilizing a class interval technique (i.e. histogram) to maintain a bunch of representative samples from each bin. …”
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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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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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Blue collar laborers’ travel pattern recognition: Machine learning classifier approach
Published 2021“…The research methodology undertaken in this paper comprises a combination of different machine learning techniques, predominantly by applying clustering and classification methods. A bagged Clustering algorithm was employed to identify the number of clusters, then the C-Means algorithm and the Pamk algorithm were implemented to validate the results. …”
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A Fully Optical Laser Based System for Damage Detection and Localization in Rail Tracks Using Ultrasonic Rayleigh Waves: A Numerical and Experimental Study
Published 2022“…Further, As the quality of received signals differs at different sensing points as a result of the surface conditions of the specimen, the Self Adaptive Smart Algorithm (SASA) method was adopted to filter out the noise and accurately pinpoint the defect reflected wave packet which ultimately aids in better detection and localization. …”
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327
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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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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Software-Defined-Networking-Based One-versus-Rest Strategy for Detecting and Mitigating Distributed Denial-of-Service Attacks in Smart Home Internet of Things Devices
Published 2024“…We employed an ML method based on Random Forest (RF), Logistic Regression (LR), k-Nearest Neighbors (kNN), and Naive Bayes (NB) with a One-versus-Rest (OvR) strategy and then compared our work to other related works. …”
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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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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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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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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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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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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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Artificial Intelligence (AI) based machine learning models predict glucose variability and hypoglycaemia risk in patients with type 2 diabetes on a multiple drug regimen who fast d...
Published 2020“…<h3>Objective</h3><p dir="ltr">To develop a machine-based algorithm from clinical and demographic data, physical activity and glucose variability to predict hyperglycaemic and hypoglycaemic excursions in patients with type 2 diabetes on multiple glucose lowering therapies who fast during Ramadan.…”
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A Navigation System for Indoor/Outdoor Environments with an Unmanned Ground Vehicle (UGV)
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Developing a framework for using face recognition in transit payment transactions
Published 2021“…The proposed framework involves the hardware, software, algorithms, and system specification requirements. Further, it provides a detailed end-to-end systems integration and transaction flow between the account-based ticketing, face recognition, and banking systems. …”
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