Network intrusion detection system: A systematic study of machine learning and deep learning approaches
The rapid advances in the internet and communication fields have resulted in a huge
increase in the network size and the corresponding data. As a result, many novel attacks are …
increase in the network size and the corresponding data. As a result, many novel attacks are …
Boosting methods for multi-class imbalanced data classification: an experimental review
Since canonical machine learning algorithms assume that the dataset has equal number of
samples in each class, binary classification became a very challenging task to discriminate …
samples in each class, binary classification became a very challenging task to discriminate …
A survey on machine learning techniques for cyber security in the last decade
Pervasive growth and usage of the Internet and mobile applications have expanded
cyberspace. The cyberspace has become more vulnerable to automated and prolonged …
cyberspace. The cyberspace has become more vulnerable to automated and prolonged …
[HTML][HTML] A hybrid CNN+ LSTM-based intrusion detection system for industrial IoT networks
Abstract The Internet of Things (IoT) ecosystem has proliferated based on the use of the
internet and cloud-based technologies in the industrial area. IoT technology used in the …
internet and cloud-based technologies in the industrial area. IoT technology used in the …
A review of data-driven fault detection and diagnostics for building HVAC systems
With the wide adoption of building automation system, and the advancement of data,
sensing, and machine learning techniques, data-driven fault detection and diagnostics …
sensing, and machine learning techniques, data-driven fault detection and diagnostics …
Three-way confusion matrix for classification: A measure driven view
J Xu, Y Zhang, D Miao - Information sciences, 2020 - Elsevier
Abstract Three-way decisions (3WD) is an important methodology in solving problems with
uncertainty. A systematic analysis on three-way based uncertainty measures is conducive to …
uncertainty. A systematic analysis on three-way based uncertainty measures is conducive to …
Advances in computational intelligence of polymer composite materials: machine learning assisted modeling, analysis and design
The superior multi-functional properties of polymer composites have made them an ideal
choice for aerospace, automobile, marine, civil, and many other technologically demanding …
choice for aerospace, automobile, marine, civil, and many other technologically demanding …
Deep-net: A lightweight CNN-based speech emotion recognition system using deep frequency features
Artificial intelligence (AI) and machine learning (ML) are employed to make systems smarter.
Today, the speech emotion recognition (SER) system evaluates the emotional state of the …
Today, the speech emotion recognition (SER) system evaluates the emotional state of the …
Vectorized rooftop area data for 90 cities in China
Reliable information on building rooftops is crucial for utilizing limited urban space
effectively. In recent decades, the demand for accurate and up-to-date data on the areas of …
effectively. In recent decades, the demand for accurate and up-to-date data on the areas of …
Automatic fault classification in photovoltaic modules using Convolutional Neural Networks
Photovoltaic (PV) power systems have a significant potential to reduce greenhouse gases
and diversify the electricity generation mix. Faults and damages that cause energy losses …
and diversify the electricity generation mix. Faults and damages that cause energy losses …