Machine learning for coverage optimization in wireless sensor networks: a comprehensive review
In the context of wireless sensor networks (WSNs), the utilization of artificial intelligence (AI)-
based solutions and systems is on the ascent. These technologies offer significant potential …
based solutions and systems is on the ascent. These technologies offer significant potential …
[HTML][HTML] Deep learning and data fusion to estimate surface soil moisture from multi-sensor satellite images
We propose a new architecture based on a fully connected feed-forward Artificial Neural
Network (ANN) model to estimate surface soil moisture from satellite images on a large …
Network (ANN) model to estimate surface soil moisture from satellite images on a large …
A Survey on Graph Neural Networks for Intrusion Detection Systems: Methods, Trends and Challenges
Intrusion detection systems (IDS) play a crucial role in maintaining network security. With the
increasing sophistication of cyber attack methods, traditional detection approaches are …
increasing sophistication of cyber attack methods, traditional detection approaches are …
AutoML-GWL: Automated machine learning model for the prediction of groundwater level
Predicting groundwater levels is pivotal in curbing overexploitation and ensuring effective
water resource governance. However, groundwater level prediction is intricate, driven by …
water resource governance. However, groundwater level prediction is intricate, driven by …
Stochastic gradient descent classifier-based lightweight intrusion detection systems using the efficient feature subsets of datasets
J Azimjonov, T Kim - Expert Systems with Applications, 2024 - Elsevier
Abstract The Internet of Things (IoT) has become an essential part of our daily lives.
However, with the increasing use of IoT, the number of botnet attacks targeting resource …
However, with the increasing use of IoT, the number of botnet attacks targeting resource …
The use of Google community mobility reports to model residential waste generation behaviors during and after the COVID-19 lockdown
This paper proposed an original analytical approach to quantify waste generation and
recycling behaviors in Regina, a Canadian capital city, using Google's Community Mobility …
recycling behaviors in Regina, a Canadian capital city, using Google's Community Mobility …
P2CA-GAM-ID: Coupling of probabilistic principal components analysis with generalised additive model to predict the k− barriers for intrusion detection
Drastic advancement in computing technology and the dramatic increase in the usage of
explainable machine learning algorithms provide a promising platform for developing robust …
explainable machine learning algorithms provide a promising platform for developing robust …
Design of advanced intrusion detection systems based on hybrid machine learning techniques in hierarchically wireless sensor networks
Wireless sensor networks (WSNs) are an emerging military and civilian technology that uses
sensors. Sensor networks are hierarchical and chaotic in remote, unmonitored sites …
sensors. Sensor networks are hierarchical and chaotic in remote, unmonitored sites …
F-TLBO-ID: Fuzzy fed teaching learning based optimisation algorithm to predict the number of k-barriers for intrusion detection
Ensuring fast and efficient Intrusion Detection and Prevention (IDP) at international borders
is crucial for maintaining security and safeguarding nations. In this study, we propose an …
is crucial for maintaining security and safeguarding nations. In this study, we propose an …
Probabilistic intrusion detection based on an optimal strong K-barrier strategy in WSNs
Ensuring better surveillance of borders with K-barrier coverage type via homogeneous
wireless sensor networks (WSNs) remains a challenging task to be solved urgently since it …
wireless sensor networks (WSNs) remains a challenging task to be solved urgently since it …