Search Results - (( intelligence study learning algorithm ) OR ( intelligence system matching algorithm ))

Energy management strategies, control systems, and artificial intelligence-based algorithms development for hydrogen fuel cell-powered vehicles: A review by Oladosu T.L., Pasupuleti J., Kiong T.S., Koh S.P.J., Yusaf T.

“…Therefore, this study presents the prospect of artificial intelligence-based algorithms, control systems, and energy management strategies advances on HFCEVs performance optimization. …”

Music Recommender System Using Machine Learning Content-Based Filtering Technique by Foong, Kin Hong

“…Machine Learning is a form of Artificial Intelligence that will make systems to think like human being. …”
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Enhancement of network security by use machine learning by Hasan, Ahmed Raheem

“…The important study in this research is the machine learning with deep learning system to enhance the security. …”
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Trends on technologies and artificial intelligence in education for personalized learning: systematic literature review by Hashim, Suraya, Omar, Muhd Khaizer, Ab. Jalil, Habibah, Mohd Sharef, Nurfadhlina

“…The research and practices reported in the study also show how personalized learning was used and factors that made it work, thus the finding of this paper will guide other researchers to recognize various personal traits and the identification of appropriate technology trends and activities for further studies, as well as assist developers in the development of the personalized learning system and closely related to the adaptive learning systems.…”
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Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks by Mohammed Aswad, Firas, Saleh Ahmed,, Ali Mohammed, Ali Majeed Alhammadi, Nafea, Ahmad Khalaf, Bashar, A. Mostafa, Salama

“…The main ongoing research issue is developing a model capable of protecting the network from DDoS attacks that is sensitive to various classes of DDoS and can recognize legitimate traffic to avoid false alarms. Subsequently, this study proposes combining three deep learning algorithms, namely recurrent neural network (RNN), long short-term memory (LSTM)-RNN, and convolutional neural network (CNN), to build a bidirectional CNN-BiLSTM DDoS detection model. …”
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Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks by Mohammed Aswad, Firas, Ahmed, Ali Mohammed Saleh, Majeed Alhammadi, Nafea Ali, Ahmad Khalaf, Bashar, A. Mostafa, Salama

“…The main ongoing research issue is developing a model capable of protecting the network from DDoS attacks that is sensitive to various classes of DDoS and can recognize legitimate traffic to avoid false alarms. Subsequently, this study proposes combining three deep learning algorithms, namely recurrent neural network (RNN), long short-term memory (LSTM)-RNN, and convolutional neural network (CNN), to build a bidirectional CNN-BiLSTM DDoS detection model. …”
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Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks by Mohammed Aswad, Firas, Saleh Ahmed, Ali Mohammed, Ali Majeed Alhammadi, Nafea, Ahmad Khalaf, Bashar, A. Mostafa, Salama

“…The main ongoing research issue is developing a model capable of protecting the network from DDoS attacks that is sensitive to various classes of DDoS and can recognize legitimate traffic to avoid false alarms. Subsequently, this study proposes combining three deep learning algorithms, namely recurrent neural network (RNN), long short-term memory (LSTM)-RNN, and convolutional neural network (CNN), to build a bidirectional CNN-BiLSTM DDoS detection model. …”
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Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks by Firas Mohammed Aswad, Firas Mohammed Aswad, Ali Mohammed Saleh Ahmed, Ali Mohammed Saleh Ahmed, Nafea Ali Majeed Alhammadi, Nafea Ali Majeed Alhammadi, Bashar Ahmad Khalaf, Bashar Ahmad Khalaf, Salama A. Mostafa, Salama A. Mostafa

“…The main ongoing research issue is developing a model capable of protecting the network from DDoS attacks that is sensitive to various classes of DDoS and can recognize legitimate traffic to avoid false alarms. Subsequently, this study proposes combining three deep learning algorithms, namely recurrent neural network (RNN), long short-term memory (LSTM)-RNN, and convolutional neural network (CNN), to build a bidirectional CNN-BiLSTM DDoS detection model. …”
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Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks by Mohammed Aswad, Firas, Ahmed, Ali Mohammed Saleh, Ali Majeed Alhammadi, Nafea, Bashar Ahmad Khalaf, Bashar Ahmad Khalaf, Salama A. Mostafa, Salama A. Mostafa

“…The main ongoing research issue is developing a model capable of protecting the network from DDoS attacks that is sensitive to various classes of DDoS and can recognize legitimate traffic to avoid false alarms. Subsequently, this study proposes combining three deep learning algorithms, namely recurrent neural network (RNN), long short-term memory (LSTM)-RNN, and convolutional neural network (CNN), to build a bidirectional CNN-BiLSTM DDoS detection model. …”
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Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks by Firas Mohammed Aswad, Firas Mohammed Aswad, Ali Mohammed Saleh Ahmed, Ali Mohammed Saleh Ahmed, Nafea Ali Majeed Alhammadi, Nafea Ali Majeed Alhammadi, Bashar Ahmad Khalaf, Bashar Ahmad Khalaf, Salama A. Mostafa, Salama A. Mostafa

“…The main ongoing research issue is developing a model capable of protecting the network from DDoS attacks that is sensitive to various classes of DDoS and can recognize legitimate traffic to avoid false alarms. Subsequently, this study proposes combining three deep learning algorithms, namely recurrent neural network (RNN), long short-term memory (LSTM)-RNN, and convolutional neural network (CNN), to build a bidirectional CNN-BiLSTM DDoS detection model. …”
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Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks by Firas Mohammed Aswad, Firas Mohammed Aswad, Ali Mohammed Saleh Ahmed, Ali Mohammed Saleh Ahmed, Nafea Ali Majeed Alhammadi, Nafea Ali Majeed Alhammadi, Bashar Ahmad Khalaf, Bashar Ahmad Khalaf, Salama A. Mostafa, Salama A. Mostafa

“…The main ongoing research issue is developing a model capable of protecting the network from DDoS attacks that is sensitive to various classes of DDoS and can recognize legitimate traffic to avoid false alarms. Subsequently, this study proposes combining three deep learning algorithms, namely recurrent neural network (RNN), long short-term memory (LSTM)-RNN, and convolutional neural network (CNN), to build a bidirectional CNN-BiLSTM DDoS detection model. …”
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Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks by Mohammed Aswad, Firas, Mohammed Saleh Ahmed, Ali, Ali Majeed Alhammadi,, Nafea, Ahmad Khalaf, Bashar, Mostafa, Salama A.

“…The main ongoing research issue is developing a model capable of protecting the network from DDoS attacks that is sensitive to various classes of DDoS and can recognize legitimate traffic to avoid false alarms. Subsequently, this study proposes combining three deep learning algorithms, namely recurrent neural network (RNN), long short-term memory (LSTM)-RNN, and convolutional neural network (CNN), to build a bidirectional CNN-BiLSTM DDoS detection model. …”
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Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks by Mohammed Aswad, Firas, Ahmed, Ali Mohammed Saleh, Ali Majeed Alhammadi, Nafea Ali Majeed Alhammadi, Khalaf, Bashar Ahmad, Mostafa, Salama A.

“…The main ongoing research issue is developing a model capable of protecting the network from DDoS attacks that is sensitive to various classes of DDoS and can recognize legitimate traffic to avoid false alarms. Subsequently, this study proposes combining three deep learning algorithms, namely recurrent neural network (RNN), long short-term memory (LSTM)-RNN, and convolutional neural network (CNN), to build a bidirectional CNN-BiLSTM DDoS detection model. …”
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Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks by Firas Mohammed Aswad, Firas Mohammed Aswad, Ali Mohammed Saleh Ahmed, Ali Mohammed Saleh Ahmed, Nafea Ali Majeed Alhammadi, Nafea Ali Majeed Alhammadi, Bashar Ahmad Khalaf, Bashar Ahmad Khalaf, Salama A. Mostafa, Salama A. Mostafa

“…The main ongoing research issue is developing a model capable of protecting the network from DDoS attacks that is sensitive to various classes of DDoS and can recognize legitimate traffic to avoid false alarms. Subsequently, this study proposes combining three deep learning algorithms, namely recurrent neural network (RNN), long short-term memory (LSTM)-RNN, and convolutional neural network (CNN), to build a bidirectional CNN-BiLSTM DDoS detection model. …”
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Anomaly detection for vision-based inspection by Chew, Yan Zhe

“…There are two approaches to visual inspection: the conventional approach which uses image processing techniques and the modern AI-based approach through deep learning. This study aims to implement visual inspection systems using both approaches and determine the suitability of each approach for visual anomaly detection. …”
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A Novel Map-matching Algorithm to Improve Vehicle Tracking System Accuracy by Dewandaru, Agung, Md Said, Abas, Matori, A. N.

“…The curve-to-curve matching algorithms measure the similarity between the track and possible road path. …”
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A novel map-matching algorithm to improve vehicle tracking system accuracy by A.M., Said, A.N., Matori, A., Dewandaru

“…Map-matching algorithms attempt to pinpoint the vehicle in a particular road map segment (or any restricting track such as rails, etc), in spite of the digital map errors and navigation system inaccuracies. …”
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Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation by Mat Jani H., Lee S.P.

“…The main objective of this paper is to propose and implement an intelligent framework documentation approach that integrates case-based learning (CBL) with genetic algorithm (GA) and Knuth-Morris-Pratt (KMP) pattern matching algorithm with the intention of making learning a framework more effective. …”

A Map-matching Algorithm to Improve Vehicle Tracking Systems Accuracy by Dewandaru, Agung

“…Keywords: map-matching, vehicle tracking systems, Multiple Hypotheses Technique, Global Positioning System.…”
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A Map-matching Algorithm to Improve Vehicle Tracking Systems Accuracy by Agung Dewandaru, Agung

“…Keywords: map-matching, vehicle tracking systems, Multiple Hypotheses Technique, Global Positioning System.…”
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