بدائل البحث:
learning algorithm » learning algorithms (توسيع البحث)
code algorithm » cosine algorithm (توسيع البحث), rd algorithm (توسيع البحث), colony algorithm (توسيع البحث)
per algorithm » deer algorithm (توسيع البحث), rd algorithm (توسيع البحث), search algorithm (توسيع البحث)
elements per » elementi per (توسيع البحث), elements _ (توسيع البحث)
learning algorithm » learning algorithms (توسيع البحث)
code algorithm » cosine algorithm (توسيع البحث), rd algorithm (توسيع البحث), colony algorithm (توسيع البحث)
per algorithm » deer algorithm (توسيع البحث), rd algorithm (توسيع البحث), search algorithm (توسيع البحث)
elements per » elementi per (توسيع البحث), elements _ (توسيع البحث)
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161
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163
Identification of phantom movements with an ensemble learning approach
منشور في 2022"…The ensemble learning-based approaches outperformed the SVM, Decision tree, and kNN methods. …"
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164
EEG-Based Multi-Modal Emotion Recognition using Bag of Deep Features: An Optimal Feature Selection Approach
منشور في 2019"…<p dir="ltr">Much attention has been paid to the recognition of human emotions with the help of electroencephalogram (EEG) signals based on machine learning technology. Recognizing emotions is a challenging task due to the non-linear property of the EEG signal. …"
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165
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166
Recursive least-squares backpropagation algorithm for stop-and-go decision-directed blind equalization
منشور في 2002"…To overcome this problem, in this work, a fast converging recursive least squares (RLS)-based complex-valued backpropagation learning algorithm is derived for S&G-DD blind equalization. …"
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article -
167
Joint energy-distortion aware algorithms for cooperative video streaming over LTE networks
منشور في 2013"…Videos with single description coding (SDC), multiple description coding (MDC), and scalable video coding (SVC) are considered. …"
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احصل على النص الكامل
احصل على النص الكامل
article -
168
Adaptive Secure Pipeline for Attacks Detection in Networks with set of Distribution Hosts
منشور في 2022"…The research work carried out, in relation to attack detection ensemble learning, mainly aims to increase the performance of machine learning algorithms by combining their results. …"
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169
A machine learning approach for localization in cellular environments
منشور في 2018"…A machine learning approach is developed for localization based on received signal strength (RSS) from cellular towers. …"
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احصل على النص الكامل
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احصل على النص الكامل
conferenceObject -
170
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171
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172
LDSVM: Leukemia Cancer Classification Using Machine Learning
منشور في 2022"…This study proposes a novel method using machine learning algorithms based on microarrays of leukemia GSE9476 cells. …"
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173
Using machine learning to support students’ academic decisions
منشور في 2019"…This research tests and compares the performance of Decision Trees, Random Forests, Gradient-Boosted trees, and Deep Learning machine learning regression algorithms to predict student GPA. …"
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174
Cyberbullying Detection in Arabic Text using Deep Learning
منشور في 2023"…Data-driven approaches, such as machine learning (ML), particularly deep learning (DL), have shown promising results. …"
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175
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176
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177
Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management
منشور في 2019احصل على النص الكامل
doctoralThesis -
178
Single channel speech denoising by DDPG reinforcement learning agent
منشور في 2025"…In this paper, a novel SD algorithm is presented based on the deep deterministic policy gradient (DDPG) agent; an off-policy reinforcement learning (RL) agent with a continuous action space. …"
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179
Analysis of Using Machine Learning to Enhance the Efficiency of Facilities Management in the UAE
منشور في 2022"…This study addresses these issues by Implementing Machine Learning (ML) algorithms using data from Building Management Systems (BMS) and FM maintenance reports, focussing on predictive maintenance for Fresh Air Handling Units. …"
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180
The Role of Machine Learning in Diagnosing Bipolar Disorder: Scoping Review
منشور في 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%). …"