Deep-Learning Approach to the Detection and Localization of Cyber-Physical Attacks on Water Distribution Systems-Reference-Cited by-同舟云学术

Deep-Learning Approach to the Detection and Localization of Cyber-Physical Attacks on Water Distribution Systems

Published:2018-10 Issue:10 Volume:144 Page:04018065
ISSN:0733-9496
Container-title:Journal of Water Resources Planning and Management
language:en
Short-container-title:J. Water Resour. Plann. Manage.

Author:

Taormina Riccardo¹,Galelli Stefano²

Affiliation:

1. Postdoctoral Research Fellow, Pillar of Engineering Systems and Design, Singapore Univ. of Technology and Design, 8 Somapah Rd., Singapore 487372, Singapore (corresponding author).

2. Assistant Professor, Pillar of Engineering Systems and Design, Singapore Univ. of Technology and Design, 8 Somapah Rd., Singapore 487372, Singapore.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Management, Monitoring, Policy and Law,Water Science and Technology,Geography, Planning and Development,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29WR.1943-5452.0000983

Reference41 articles.

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3. Generalization performance of support vector machines and neural networks in runoff modeling

4. Learning Deep Architectures for AI

5. Chen T. and C. Guestrin. 2016. “XGBoost: A scalable tree boosting system.” In Proc. 22nd ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining 785–794. New York: ACM.

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