Intelligent techniques for detecting network attacks: review and research directions
The significant growth in the use of the Internet and the rapid development of network
technologies are associated with an increased risk of network attacks. Network attacks refer …
technologies are associated with an increased risk of network attacks. Network attacks refer …
An appraisal of incremental learning methods
As a special case of machine learning, incremental learning can acquire useful knowledge
from incoming data continuously while it does not need to access the original data. It is …
from incoming data continuously while it does not need to access the original data. It is …
Physics-informed deep learning for musculoskeletal modeling: Predicting muscle forces and joint kinematics from surface EMG
Musculoskeletal models have been widely used for detailed biomechanical analysis to
characterise various functional impairments given their ability to estimate movement …
characterise various functional impairments given their ability to estimate movement …
Cooperative USV–UAV marine search and rescue with visual navigation and reinforcement learning-based control
This paper investigates visual navigation and control of a cooperative unmanned surface
vehicle (USV)-unmanned aerial vehicle (UAV) system for marine search and rescue. First, a …
vehicle (USV)-unmanned aerial vehicle (UAV) system for marine search and rescue. First, a …
DsP-YOLO: An anchor-free network with DsPAN for small object detection of multiscale defects
Industrial defect detection is of great significance to ensure the quality of industrial products.
The surface defects of industrial products are characterized by multiple scales, multiple …
The surface defects of industrial products are characterized by multiple scales, multiple …
Sentiment analysis and emotion detection on cryptocurrency related tweets using ensemble LSTM-GRU model
The cryptocurrency market has been developed at an unprecedented speed over the past
few years. Cryptocurrency works similar to standard currency, however, virtual payments are …
few years. Cryptocurrency works similar to standard currency, however, virtual payments are …
A data-driven physics-constrained deep learning computational framework for solving von Mises plasticity
Current work presents an efficient data-driven Physics Informed Neural Networks (PINNs)
computational framework for the solution of elastoplastic solid mechanics. To incorporate …
computational framework for the solution of elastoplastic solid mechanics. To incorporate …
An ensemble of a boosted hybrid of deep learning models and technical analysis for forecasting stock prices
For several years the modeling as well as forecasting of the prices of stocks have been
extremely challenging for the business community and researchers as a result of the …
extremely challenging for the business community and researchers as a result of the …
[HTML][HTML] Improved LSTM-based deep learning model for COVID-19 prediction using optimized approach
L Zhou, C Zhao, N Liu, X Yao, Z Cheng - Engineering applications of …, 2023 - Elsevier
Individuals in any country are badly impacted both economically and physically whenever
an epidemic of infectious illnesses breaks out. A novel coronavirus strain was responsible …
an epidemic of infectious illnesses breaks out. A novel coronavirus strain was responsible …
Modeling the Stackelberg game with a boundedly rational follower in deterioration supply chain-based interaction with the leader's hybrid pricing strategy
N Khanlarzade, H Farughi - Expert Systems with Applications, 2024 - Elsevier
In the conventional Stackelberg game, all players are perfect optimizers, able to choose the
best responses to their competitors' decisions. In contrast, in the Stackelberg game with …
best responses to their competitors' decisions. In contrast, in the Stackelberg game with …