A deep learning approach to predict the number of k-barriers

版本 1.0.2 (1.9 MB) 作者: ABHILASH SINGH
MATLAB code for "A deep learning approach to predict the number of k-barriers for intrusion detection over a circular region using WSNs."
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更新时间 2022/8/26
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This file contains the MATLAB code for "A deep learning approach to predict the number of k-barriers for intrusion detection over a circular region using WSNs, 2022, Expert Systems with Applications."
For more information please refer to the following link;
https://doi.org/10.1016/j.eswa.2022.118588
If you need a full-text of this manuscript then please email to me (abhilash.iiserb@gmail.com) or you can request it through ResearchGate.
If you are using this code then please cite the following paper;
Singh, A., Amutha, J., Nagar, J., & Sharma, S. (2022). A deep learning approach to predict the number of k-barriers for intrusion detection over a circular region using wireless sensor networks. Expert Systems with Applications, 118588.
Additional references for further reading;
  1. Singh, A., Nagar, J., Sharma, S., & Kotiyal, V. (2021). A Gaussian process regression approach to predict the k-barrier coverage probability for intrusion detection in wireless sensor networks. Expert Systems with Applications, 172, 114603. https://doi.org/10.1016/j.eswa.2021.114603
  2. Singh, A., Amutha, J., Nagar, J., Sharma, S., & Lee, C. C. (2022). Lt-fs-id: Log-transformed feature learning and feature-scaling-based machine learning algorithms to predict the k-barriers for intrusion detection using wireless sensor network. Sensors, 22(3), 1070. https://doi.org/10.3390/s22031070
  3. Singh, A., Amutha, J., Nagar, J., Sharma, S., & Lee, C. C. (2022). AutoML-ID: automated machine learning model for intrusion detection using wireless sensor network. Scientific Reports, 12(1), 1-14. https://www.nature.com/articles/s41598-022-13061-z

引用格式

ABHILASH SINGH (2024). A deep learning approach to predict the number of k-barriers (https://github.com/abhilash12iec002/intrusion_detection/releases/tag/v1.0.2), GitHub. 检索时间: .

Singh, A., Amutha, J., Nagar, J., & Sharma, S. (2022). A deep learning approach to predict the number of k-barriers for intrusion detection over a circular region using wireless sensor networks. Expert Systems with Applications, 118588.

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版本 已发布 发行说明
1.0.2

See release notes for this release on GitHub: https://github.com/abhilash12iec002/intrusion_detection/releases/tag/v1.0.2
1.0.0

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要查看或报告此来自 GitHub 的附加功能中的问题，请访问其 GitHub 仓库。