Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Liu, Yong"'
Publikováno v:
2020 5th IEEE International Conference on Big Data Analytics (ICBDA).
In the context of exponential growth of data information, a large amount of data needs to be effectively processed in the power system intranet to analyze and obtain valuable information. Among them, user behavior is especially important for the secu
Autor:
Juan Wang, Haoxi Zhang, Cesar Sanin, Gao Lulu, Edward Szczerbicki, Xu Xiang, Fei Li, Liu Yong
Publikováno v:
Cybernetics and Systems. 49:412-419
In this paper, we propose a novel intrusion detection approach using past driving experience and the neural knowledge DNA for in-vehicle information system security. The neural knowledge DNA is a novel knowledge representation method designed to supp
Publikováno v:
Electronics
Volume 9
Issue 10
Electronics, Vol 9, Iss 1631, p 1631 (2020)
Volume 9
Issue 10
Electronics, Vol 9, Iss 1631, p 1631 (2020)
With the rapid development of the Internet, malware traffic is seriously endangering the security of cyberspace. Convolutional neural networks (CNNs)-based malware traffic classification can automatically learn features from raw traffic, avoiding the
Publikováno v:
CSCWD
We herein propose an evolutionary multi-agent system (EMAS for short) to build an ensemble of surrogates for prediction. In our EMAS, we employ six kinds of basic surrogates, including Gaussian process, Kriging model, polynomial response surface, rad
Publikováno v:
American Journal of Electrical Power and Energy Systems. 5:51
The research on the self-healing system in smart grid is a worldwide research topic, and it has very important significance for the safe and stable operation of the power grid. The research topic was proposed by America Electric Power Science Researc
Publikováno v:
ICNC-FSKD
Masum, S, Liu, Y & Chiverton, J 2018, Comparative analysis of the outcomes of differing time series forecasting strategies . in Y Liu, L Zhao, G Cai, G Xiao, K Li & L Wang (eds), 2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) . Institute of Electrical and Electronics Engineers, Guilin, pp. 1964-1968 . https://doi.org/10.1109/FSKD.2017.8393069
Masum, S, Liu, Y & Chiverton, J 2018, Comparative analysis of the outcomes of differing time series forecasting strategies . in Y Liu, L Zhao, G Cai, G Xiao, K Li & L Wang (eds), 2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) . Institute of Electrical and Electronics Engineers, Guilin, pp. 1964-1968 . https://doi.org/10.1109/FSKD.2017.8393069
Time series forecasting of data from various domains has become an increasingly interesting research subject in recent times. Prediction of future sample values is the main goal of time series forecasting. There are mainly two classes of time series