Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Keishiro Watanabe"'
Publikováno v:
2023 International Conference on Computing, Networking and Communications (ICNC).
Publikováno v:
ICAIIC
In this paper, we propose a data-driven and end-to- end deep reinforcement learning-based method for delivering fuel to telecommunication exchange buildings right after large-scale disasters in order to restore or continue their services. Specificall
Publikováno v:
ICDCS
Because automatic recovery from failures is of great importance for future operations of ICT systems, we propose a framework for learning a recovery policy using deep reinforcement learning. In our framework, while iteratively trying various recovery
Autor:
Tsutomu Hirao, Akio Watanabe, Hiroki Ikeuchi, Yoichi Matsuo, Keishiro Watanabe, Makoto Morishita, Masaaki Nishino
Publikováno v:
NOMS
With the increase in scale and complexity of ICT systems, their operation increasingly requires automatic recovery from failures. Although it has become possible to automatically detect anomalies and analyze root causes of failures with current metho
Publikováno v:
NOMS
Health monitoring is important for maintaining reliable information and communications technology (ICT) systems. Anomaly detection methods based on machine learning, which train a model for describing "normality" are promising for monitoring the stat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::44115f7f978ba3abce9eb47e6150ed3a
Publikováno v:
IEICE Communications Society Magazine. 12:29-38
Autor:
Tsuyoshi Toyono, Akio Watanabe, Yoichi Matsuo, Keishiro Watanabe, Kohei Shiomoto, Ryoichi Kawahara, Tatsuaki Kimura, Keisuke Ishibashi
Publikováno v:
IEICE Transactions on Information and Systems. :1030-1041
Autor:
Yoichi Matsuo, Keishiro Watanabe, Akio Watanabe, Ryoichi Kawahara, Keisuke Ishibashi, Yuusuke Nakano
Publikováno v:
ICC
We propose a root-cause diagnosis method for finding equipment suffering from rare failures in a communication network. Although many studies have been conducted on root cause diagnosis for finding failed equipment using a Bayesian Network or other m
Autor:
Keisuke Ishibashi, Kohei Shiomoto, Akio Watanabe, Tatsuaki Kimura, Yoichi Matsuo, Keishiro Watanabe, Tsuyoshi Toyono
Publikováno v:
NOMS
In current large scale networks, troubleshooting has become more complicated task due to the diversification in the causes of network failures. The increase in the operational costs has become a serious problem. Thus, manualization of the troubleshoo
Autor:
Keishiro Watanabe1, Yasuhiro Ikeda2, Yuusuke Nakano3, Keisuke Ishibashi4, Ryoichi Kawahara5, Satoshi Suzuki6
Publikováno v:
NTT Technical Review. Jun2018, Vol. 16 Issue 6, p1-7. 7p.