scholarly journals Predicting the rate of inbreeding in populations undergoing four-path selection on genomically enhanced breeding values

2022 ◽  
Author(s):  
Kenji Togashi ◽  
Kazunori Adachi ◽  
Kazuhito Kurogi ◽  
Takanori Yasumori ◽  
Toshio Watanabe ◽  
...  
Keyword(s):  
Path Selection ◽  
Breeding Values

Asymptotic response to four-path selection due to index and single trait selection according to genomically enhanced breeding values

2020 ◽  
Vol 231 ◽  
pp. 103846
Author(s):  
Togashi Kenji ◽  
Kazuhito Kurogi ◽  
Kazunori Adachi ◽  
Kota Tokunaka ◽  
Takanori Yasumori ◽  
...  
Keyword(s):  
Path Selection ◽  
Breeding Values

Resource-Aware Path Selection in Heterogeneous Self-Organizing Wireless Networks

2010 ◽  
Vol E93-B (12) ◽  
pp. 3647-3650
Author(s):  
Bongjhin SHIN ◽  
Hoyoung CHOI ◽  
Daehyoung HONG
Keyword(s):  
Wireless Networks ◽  
Path Selection ◽  
Resource Aware ◽  
Self Organizing

Estimation of parameters and breeding values for growth traits of largemouth bass

2013 ◽  
Vol 18 (4) ◽  
pp. 766-773
Author(s):  
Rong LI ◽  
Junjie BAI ◽  
Shengjie LI ◽  
jiexiang WANG ◽  
Xing YE
Keyword(s):  
Largemouth Bass ◽  
Growth Traits ◽  
Estimation Of Parameters ◽  
Breeding Values

scholarly journals Network Attack Path Selection and Evaluation Based on Q-Learning

2020 ◽  
Vol 11 (1) ◽  
pp. 285
Author(s):  
Runze Wu ◽  
Jinxin Gong ◽  
Weiyue Tong ◽  
Bing Fan
Keyword(s):  
Distribution System ◽  
Path Selection ◽  
Cyber Attacks ◽  
Power Distribution System ◽  
Q Learning ◽  
Attack Model ◽  
Cross Domain ◽  
Time Operation ◽  
Attack Path ◽  
The Impact

As the coupling relationship between information systems and physical power grids is getting closer, various types of cyber attacks have increased the operational risks of a power cyber-physical System (CPS). In order to effectively evaluate this risk, this paper proposed a method of cross-domain propagation analysis of a power CPS risk based on reinforcement learning. First, the Fuzzy Petri Net (FPN) was used to establish an attack model, and Q-Learning was improved through FPN. The attack gain was defined from the attacker’s point of view to obtain the best attack path. On this basis, a quantitative indicator of information-physical cross-domain spreading risk was put forward to analyze the impact of cyber attacks on the real-time operation of the power grid. Finally, the simulation based on Institute of Electrical and Electronics Engineers (IEEE) 14 power distribution system verifies the effectiveness of the proposed risk assessment method.

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