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models algorithm » mould algorithm (Expand Search), deer algorithm (Expand Search)
using algorithm » cosine algorithm (Expand Search)
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461
Identification of the Uncertainty Structure to Estimate the Acoustic Release of Chemotherapeutics From Polymeric Micelles
Published 2017“…The proposed algorithms are initially deployed in a simulation environment, and then the experimental data sets are fed into the algorithms to validate their performance. …”
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462
An Auction-Based Scheduling Approach for Minimizing Latency in Fog Computing Using 5G Infrastructure
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doctoralThesis -
463
A Digital DNA Sequencing Engine for Ransomware Analysis using a Machine Learning Network
Published 2020“…The data is finally classified as either ransomware or goodware using the learning methodologies. …”
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464
Multimodal feature fusion and ensemble learning for non-intrusive occupancy monitoring using smart meters
Published 2025“…In this study, we introduce the multimodal feature fusion for non-intrusive occupancy monitoring (MMF-NIOM) framework, which leverages both classical and deep machine learning algorithms to achieve state-of-the-art occupancy detection performance using smart meter data. …”
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465
Cognitive Load Estimation Using a Hybrid Cluster-Based Unsupervised Machine Learning Technique
Published 2024“…In this study, we harnessed the capabilities of a four-channel, wearable EEG device that captured brain activity data during two distinct CL states: Baseline (representing a non-CL, resting state) and the Stroop Test (a CL-inducing state). …”
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466
Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test
Published 2019“…Data generated from an oral glucose tolerance test (OGTT) was used to develop a predictive model based on the support vector machine (SVM). …”
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467
Strategies for Reliable Stress Recognition: A Machine Learning Approach Using Heart Rate Variability Features
Published 2024“…However, limited datasets in affective computing and healthcare research can lead to inaccurate conclusions regarding the ML model performance. This study employed supervised learning algorithms to classify stress and relaxation states using HRV measures. …”
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468
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469
Ensemble Deep Random Vector Functional Link Neural Network for Regression
Published 2022“…The esc-edRVFL is identified as the best-performing algorithm through a comprehensive evaluation of 31 UCI datasets.…”
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470
Lung-EffNet: Lung cancer classification using EfficientNet from CT-scan images
Published 2023“…The class imbalance issue was handled through multiple data augmentation methods to overcome the biases. …”
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471
EEG-Based Multi-Modal Emotion Recognition using Bag of Deep Features: An Optimal Feature Selection Approach
Published 2019“…To reduce the feature dimensionality, spatial, and temporal based, bag of deep features (BoDF) model is proposed. A series of vocabularies consisting of 10 cluster centers of each class is calculated using the k-means cluster algorithm. …”
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472
Predicting and Interpreting Student Performance Using Machine Learning in Blended Learning Environments in a Jordanian School Context
Published 0024“…These platforms enhance academic performance by fostering collaborative learning environments and generating extensive data from every user interaction. Machine learning algorithms can process large and complex datasets to identify patterns and trends that may not be immediately apparent. …”
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473
Electric Vehicles Charging Station Load Forecasting Integration With Renewable Energy Using Novel Deep EfficientBiLSTMNet
Published 2025“…The model’s hyperparameters are optimized using an Enhanced Firefly Algorithm (EFA). …”
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474
A Robust Deep Learning Approach for Distribution System State Estimation with Distributed Generation
Published 2023“…Also, to evaluate the robustness of the algorithms, we test the neural network, without retraining it, on multiple scenarios with noisier data and bad data. …”
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masterThesis -
475
Intelligent route to design efficient CO<sub>2</sub> reduction electrocatalysts using ANFIS optimized by GA and PSO
Published 2022“…In doing so, to represent the surface properties of the electrocatalysts numerically, d-band theory-based electronic features and intrinsic properties obtained from density functional theory (DFT) calculations were used as descriptors. Accordingly, a dataset containg 258 data points was extracted from the DFT method to use in machine learning method. …”
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476
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477
Incorporation of Robust Sliding Mode Control and Adaptive Multi-Layer Neural Network-Based Observer for Unmanned Aerial Vehicles
Published 2024“…The MLNN observer, employing a modified back-propagation algorithm, is used for the quadrotor’s state estimation. …”
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478
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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479
A Novel Partitioned Random Forest Method-Based Facial Emotion Recognition
Published 2025“…Using three statistical measures Lyapunov exponents (LE), Correlation Dimension (CD), and approximate entropy (AE), we evaluated the performance of machine learning algorithms over different data lengths. …”
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480
Detecting and Predicting Archaeological Sites Using Remote Sensing and Machine Learning—Application to the Saruq Al-Hadid Site, Dubai, UAE
Published 2023“…The modelling and prediction accuracies are expected to improve with the insertion of a neural network and backpropagation algorithms based on the performed cluster groups following more recent field surveys. …”
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