بدائل البحث:
modeling algorithm » scheduling algorithm (توسيع البحث)
learning algorithm » learning algorithms (توسيع البحث)
element learning » student learning (توسيع البحث)
using algorithm » cosine algorithm (توسيع البحث)
data modeling » data models (توسيع البحث), spatial modeling (توسيع البحث)
modeling algorithm » scheduling algorithm (توسيع البحث)
learning algorithm » learning algorithms (توسيع البحث)
element learning » student learning (توسيع البحث)
using algorithm » cosine algorithm (توسيع البحث)
data modeling » data models (توسيع البحث), spatial modeling (توسيع البحث)
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461
Face Flow: Constrained Optical Flow Framework for Faces
منشور في 2020احصل على النص الكامل
doctoralThesis -
462
Impacts of climate change on the global spread and habitat suitability of <i>Coxiella burnetii</i>: Future projections and public health implications
منشور في 2025"…</p><h3>Materials and methods</h3><p dir="ltr">An ensemble<u> species distribution modelling </u>approach, integrating regression-based and machine-learning algorithms (GLM, GBM, RF, MaxEnt), was used to project habitat suitability (Current time and by 2050, 2070, and 2090). …"
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463
EEG-Based Multi-Modal Emotion Recognition using Bag of Deep Features: An Optimal Feature Selection Approach
منشور في 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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464
Strategies for Reliable Stress Recognition: A Machine Learning Approach Using Heart Rate Variability Features
منشور في 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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465
Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test
منشور في 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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466
Multi-Modal Emotion Aware System Based on Fusion of Speech and Brain Information
منشور في 2019"…For classifying unimodal data of either speech or EEG, a hybrid fuzzy c-means-genetic algorithm-neural network model is proposed, where its fitness function finds the optimal fuzzy cluster number reducing the classification error. …"
احصل على النص الكامل
احصل على النص الكامل
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467
Lung-EffNet: Lung cancer classification using EfficientNet from CT-scan images
منشور في 2023"…The class imbalance issue was handled through multiple data augmentation methods to overcome the biases. …"
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468
Scatter search metaheuristic for homology based protein structure prediction. (c2015)
منشور في 2015"…We assess our algorithm on a total of 11 proteins whose structures are present in the Protein Data Bank (PDB) and which has been used in previous literature. …"
احصل على النص الكامل
احصل على النص الكامل
masterThesis -
469
A Robust Deep Learning Approach for Distribution System State Estimation with Distributed Generation
منشور في 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. …"
احصل على النص الكامل
احصل على النص الكامل
احصل على النص الكامل
masterThesis -
470
Predicting and Interpreting Student Performance Using Machine Learning in Blended Learning Environments in a Jordanian School Context
منشور في 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. …"
احصل على النص الكامل
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471
Electric Vehicles Charging Station Load Forecasting Integration With Renewable Energy Using Novel Deep EfficientBiLSTMNet
منشور في 2025"…The model’s hyperparameters are optimized using an Enhanced Firefly Algorithm (EFA). …"
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472
Intelligent route to design efficient CO<sub>2</sub> reduction electrocatalysts using ANFIS optimized by GA and PSO
منشور في 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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473
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474
Incorporation of Robust Sliding Mode Control and Adaptive Multi-Layer Neural Network-Based Observer for Unmanned Aerial Vehicles
منشور في 2024"…The MLNN observer, employing a modified back-propagation algorithm, is used for the quadrotor’s state estimation. …"
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475
Various Faults Classification of Industrial Application of Induction Motors Using Supervised Machine Learning: A Comprehensive Review
منشور في 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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476
A Novel Partitioned Random Forest Method-Based Facial Emotion Recognition
منشور في 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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477
Detecting and Predicting Archaeological Sites Using Remote Sensing and Machine Learning—Application to the Saruq Al-Hadid Site, Dubai, UAE
منشور في 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. …"
احصل على النص الكامل
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478
Detecting and Predicting Archaeological Sites Using Remote Sensing and Machine Learning—Application to the Saruq Al-Hadid Site, Dubai, UAE
منشور في 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. …"
احصل على النص الكامل
article -
479
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480
Smart non-intrusive appliance identification using a novel local power histogramming descriptor with an improved k-nearest neighbors classifier
منشور في 2021"…Specifically, short local histograms are drawn to represent individual appliance consumption signatures and robustly extract appliance-level data from the aggregated power signal. Furthermore, an improved k-nearest neighbors (IKNN) algorithm is presented to reduce the learning computation time and improve the classification performance. …"