بدائل البحث:
processing algorithm » processing algorithms (توسيع البحث)
machine algorithm » cosine algorithm (توسيع البحث)
method algorithm » mould algorithm (توسيع البحث)
case machine » a machine (توسيع البحث), edge machine (توسيع البحث)
element » elements (توسيع البحث)
processing algorithm » processing algorithms (توسيع البحث)
machine algorithm » cosine algorithm (توسيع البحث)
method algorithm » mould algorithm (توسيع البحث)
case machine » a machine (توسيع البحث), edge machine (توسيع البحث)
element » elements (توسيع البحث)
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121
Acoustic Based Localization of Partial Discharge Inside Oil-Filled Transformers
منشور في 2022"…<p dir="ltr">This paper addresses the localization of Partial Discharge through a 3D Finite Element Method analysis of acoustic wave propagation inside a 3-phase 35kV transformer with the help of COMSOL Multiphysics software. …"
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122
Design Optimization of Inductive Power Transfer Systems Considering Bifurcation and Equivalent AC Resistance for Spiral Coils
منشور في 2020"…Equivalent AC resistance of spiral coils is modeled based on eddy currents simulations using Finite Element Method (FEM) and Maxwell simulator. Based on the FEM simulations, a new approximation method using separation of variables is proposed as a function of spiral coil's main parameters. …"
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123
A multi-pretraining U-Net architecture for semantic segmentation
منشور في 2025"…In this research, we propose and evaluate a modified version of a deep learning algorithm called U-Net architecture for partitioning histopathological images. …"
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124
Novel Multi Center and Threshold Ternary Pattern Based Method for Disease Detection Method Using Voice
منشور في 2020"…The artificial neural network (ANN), support vector machine (SVM) and deep learning models, especially the convolutional neural network (CNN), are the most commonly used machine learning approaches where they proved to be performance in most cases. …"
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125
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126
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127
Predictive modelling in times of public health emergencies: patients’ non-transport decisions during the COVID-19 pandemic
منشور في 2025"…</p><h3>Methods</h3><p dir="ltr">Using Python® programming language, this study employed various supervised machine-learning algorithms, including parametric probabilistic models, such as logistic regression, and non-parametric models, including decision trees, random forest (RF), extra trees, AdaBoost, and k-nearest neighbours (KNN), using a dataset of non-transported patients (refused transport and did not receive treatment versus those who refused transport and received treatment) between 2018 and 2022. …"
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128
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129
Correlation Clustering with Overlaps
منشور في 2020"…In other words, data elements (or vertices) will be allowed to be members in more than one cluster instead of limiting them to only one single cluster, as in classical clustering methods. …"
احصل على النص الكامل
احصل على النص الكامل
احصل على النص الكامل
masterThesis -
130
Multi-Robot Map Exploration Based on Multiple Rapidly-Exploring Randomized Trees
منشور في 2017احصل على النص الكامل
doctoralThesis -
131
Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management
منشور في 2019احصل على النص الكامل
doctoralThesis -
132
Enhancing Breast Cancer Diagnosis With Bidirectional Recurrent Neural Networks: A Novel Approach for Histopathological Image Multi-Classification
منشور في 2025"…<p dir="ltr">In recent years, deep learning methods have dramatically improved medical image analysis, though earlier models faced difficulties in capturing intricate spatial and contextual details. …"
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133
Integrated Energy Optimization and Stability Control Using Deep Reinforcement Learning for an All-Wheel-Drive Electric Vehicle
منشور في 2025"…To evaluate the generalizability of the algorithms, the agents are tested across various velocities, tire–road friction coefficients, and additional scenarios implemented in IPG CarMaker, a high-fidelity vehicle dynamics simulator. …"
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134
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135
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136
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137
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138
Peripheral inflammatory and metabolic markers as potential biomarkers in treatment-resistant schizophrenia: Insights from a Qatari Cohort
منشور في 2024"…The Random Forest model, a supervised machine learning algorithm, efficiently differentiated between cases and controls and between TRS and NTRS, with accuracies of 86.87 % and 88.41 %, respectively. …"
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139
Next-generation energy systems for sustainable smart cities: Roles of transfer learning
منشور في 2022"…This is possible by adopting next-generation energy systems, which leverage artificial intelligence, the Internet of things (IoT), and communication technologies to collect and analyze big data in real-time and effectively run city services. However, training machine learning algorithms to perform various energy-related tasks in sustainable smart cities is a challenging data science task. …"
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140