Search alternatives:
method algorithm » mould algorithm (Expand Search)
c3 algorithm » rd algorithm (Expand Search), _ algorithms (Expand Search)
complement » implement (Expand Search), complementary (Expand Search)
finding » findings (Expand Search)
method algorithm » mould algorithm (Expand Search)
c3 algorithm » rd algorithm (Expand Search), _ algorithms (Expand Search)
complement » implement (Expand Search), complementary (Expand Search)
finding » findings (Expand Search)
-
61
Newton-Raphson based adaptive inverse control scheme for tracking of nonlinear dynamic plants
Published 2006“…The U-model is utilized to design an adaptive inverse controller by using a simple root-solving algorithm of Newton-Raphson. The synergy of U-model with AIC structure has provided an effective and straight forward method for adaptive tracking of nonlinear plants. …”
Get full text
Get full text
article -
62
A Full-System Approach of the Elastohydrodynamic Line/Point Contact Problem
Published 2008“…The use of the finite element method allows the use of variable unstructured meshing and different types of elements within the same model which leads to a reduced size of the problem. …”
Get full text
Get full text
Get full text
article -
63
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. …”
Get full text
-
64
The Frontiers of Deep Reinforcement Learning for Resource Management in Future Wireless HetNets: Techniques, Challenges, and Research Directions
Published 2022“…To this end, we carefully identify the types of DRL algorithms utilized in each related work, the elements of these algorithms, and the main findings of each related work. …”
-
65
Simulations of the penetration of 6061-T6511 aluminum targets by spherical-nosed VAR 4340 steel projectiles
Published 2000“…In the context of an analysis code, this approximation eliminates the need for discretizing the target as well as the need for a contact algorithm. Thus, this method substantially reduces the computer time and memory requirements. …”
Get full text
Get full text
Get full text
article -
66
Vibration suppression in a cantilever beam using a string-type vibration absorber
Published 2017“…The string is rigidly connected to the fixed end of the beam and through a spring and damper to a second point on the beam. The finite element method is used to model the system and a reduced order model is obtained through modal reduction performed on both the string and the beam. …”
Get full text
Get full text
Get full text
Get full text
conferenceObject -
67
Detecting Arabic Cyberbullying Tweets in Arabic Social Using Deep Learning
Published 2023“…To categorize electronic text in these two cases, deep learning models such as convolutional neural networks and recurrent neural networks and a combination of CNN-RNN were trained on this data. …”
Get full text
-
68
Sentiment Analysis of Dialectal Speech: Unveiling Emotions through Deep Learning Models
Published 2024“…Dialect Speech Sentiment Analysis is an evolutional field where machine learning algorithms are utilized to detect emotions in spoken language. …”
Get full text
-
69
Depthwise Separable Convolutions and Variational Dropout within the context of YOLOv3
Published 2020“…We also explore variational dropout: a technique that finds individual and unbounded dropout rates for each neural network weight. …”
Get full text
Get full text
Get full text
Get full text
conferenceObject -
70
Enhancing e-learning through AI: advanced techniques for optimizing student performance
Published 2024“…This research highlights the ability of AI to develop adaptable, effective, and successful e-learning environments, promoting enhanced academic achievement and customized learning experiences. The findings demonstrate that CNN outperformed other deep learning and machine learning algorithms in terms of accuracy during the prediction phase, showcasing the advanced capabilities of AI in educational contexts. …”
-
71
A comparative analysis to forecast carbon dioxide emissions
Published 2022“…Based on multivariate time series prediction, four deep learning algorithms are analyzed in this work, those are convolution neural network (CNN), CNN long short-term memory (CNN–LSTM), long short-term memory (LSTM), and dense neural network (DNN). …”
-
72
Cyberbullying Detection in Arabic Text using Deep Learning
Published 2023“…In this study, I conduct a performance evaluation and comparison for various DL algorithms (LSTM, GRU, LSTM-ATT, CNN-BLSTM, CNN-LSTM, CNN-BILSTM-LSTM, and LSTM-TCN) on different datasets of Arabic cyberbullying to obtain more precise and dependable findings. …”
Get full text
-
73
A Novel Deep Learning Technique for Detecting Emotional Impact in Online Education
Published 2022“…Transfer learning for a pre-trained deep neural network is used as well to increase the accuracy of the emotion classification stage. …”
Get full text
-
74
Combining offline and on-the-fly disambiguation to perform semantic-aware XML querying
Published 2023“…Many efforts have been deployed by the IR community to extend freetext query processing toward semi-structured XML search. Most methods rely on the concept of Lowest Comment Ancestor (LCA) between two or multiple structural nodes to identify the most specific XML elements containing query keywords posted by the user. …”
Get full text
Get full text
Get full text
Get full text
article -
75
Predicting and Interpreting Student Performance Using Machine Learning in Blended Learning Environments in a Jordanian School Context
Published 0024“…A dataset generated by a digital learning platform used by a private school in Jordan is utilised. Various ML algorithms, such as Support Vector Machines, Logistic Regression, K-Nearest Neighbors, Naïve Bayes, Decision Trees, Random Forest, AdaBoost, Bagging, and Artificial Neural Networks are applied to predict student performance. …”
Get full text
-
76
Investigating the Use of Machine Learning Models to Understand the Drugs Permeability Across Placenta
Published 2023“…<p dir="ltr">Owing to limited drug testing possibilities in pregnant population, the development of computational algorithms is crucial to predict the fate of drugs in the placental barrier; it could serve as an alternative to animal testing. …”
-
77
Developing an online hate classifier for multiple social media platforms
Published 2020“…We then experiment with several classification algorithms (Logistic Regression, Naïve Bayes, Support Vector Machines, XGBoost, and Neural Networks) and feature representations (Bag-of-Words, TF-IDF, Word2Vec, BERT, and their combination). …”
-
78
LungVision: X-ray Imagery Classification for On-Edge Diagnosis Applications
Published 2024Get full text
article -
79
Automatic Recognition of Poets for Arabic Poetry using Deep Learning Techniques (LSTM and Bi-LSTM)
Published 2024“…The reason behind selecting such models is observing a concentration on RNN (Recurrent Neural Network) and its variants when it comes to text classification. …”
Get full text
-
80
Nonlinear Friction Identification of A Linear Voice Coil DC Motor
Published 2015Get full text
doctoralThesis