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| 1 | Parallel Reinforcement Learning-Based Energy Efficiency Improvement for a Cyber-Physical System显示文摘As a complex and critical cyber-physical system(CPS),the hybrid electric powertrain is significant to mitigate air pollution and improve fuel economy.Energy management strategy(EMS)is playing a key role to improve the energy efficiency of this CPS.This paper presents a novel bidirectional long shortterm memory(LSTM)network based parallel reinforcement learning(PRL)approach to construct EMS for a hybrid tracked vehicle(HTV).This method contains two levels.The high-level establishes a parallel system first,which includes a real powertrain system and an artificial system.Then,the synthesized data from this parallel system is trained by a bidirectional LSTM network.The lower-level determines the optimal EMS using the trained action state function in the model-free reinforcement learning(RL)framework.PRL is a fully data-driven and learning-enabled approach that does not depend on any prediction and predefined rules.Finally,real vehicle testing is implemented and relevant experiment data is collected and calibrated.Experimental results validate that the proposed EMS can achieve considerable energy efficiency improvement by comparing with the conventional RL approach and deep RL. | Teng Liu Bin Tian Yunfeng Ai Fei-Yue Wang | 2020 | IEEE/CAA Journal of Automatica Sinica2020，7，2： | 14 |
| 2 | Parallel Reinforcement Learning:A Framework and Case Study显示文摘In this paper, a new machine learning framework is developed for complex system control, called parallel reinforcement learning. To overcome data deficiency of current data-driven algorithms, a parallel system is built to improve complex learning system by self-guidance. Based on the Markov chain(MC) theory, we combine the transfer learning, predictive learning, deep learning and reinforcement learning to tackle the data and action processes and to express the knowledge. Parallel reinforcement learning framework is formulated and several case studies for real-world problems are finally introduced. | Teng Liu Bin Tian Yunfeng Ai Li Li Dongpu Cao Fei-Yue Wang | 2018 | IEEE/CAA Journal of Automatica Sinica2018，5，4： | 8 |
| 3 | Preparation of Ce-PbO 2 modified electrode and its application in detection of anilines显示文摘 | Shiyun Ai Mengnan Gao Wen Zhang Qingjiang Wang Yunfeng Xie Litong Jin | 2003 | Talanta2003，，3： | 1 |
| 4 | Optimized Residual Vector Quantization for Efficient Approximate Nearest Neigh- bor Search 显示文摘 | Ai Liefu Yu Junqing He Yunfeng | 2015 | Multimedia Systems2015，，： | 1 |
| 5 | Parallel Distance: A New Paradigm of Measurement for Parallel Driving显示文摘In this paper, a new paradigm named parallel distance is presented to measure the data information in parallel driving system. As an example, the core variables in the parallel driving system are measured and evaluated in the parallel distance framework. First, the parallel driving 3.0 system included control and management platform, intelligent vehicle platform and remote-control platform is introduced. Then,Markov chain(MC) is utilized to model the transition probability matrix of control commands in these systems. Furthermore, to distinguish the control variables in artificial and physical driving conditions, different distance calculation methods are enumerated to specify the differences between the virtual and real signals. By doing this, the real system can be guided and the virtual system can be im-proved. Finally, simulation results exhibit the merits and multiple applications of the proposed parallel distance framework. | Teng Liu Hong Wang Bin Tian Yunfeng Ai Long Chen | 2020 | IEEE/CAA Journal of Automatica Sinica2020，7，4： | 0 |
| 6 | A new member of Sphenopsida,Neolobatannularia gen. nov. from Late Triassic of western Liaoning,China显示文摘A new genus Neolobatannularia Sun et Li gen. nov. with the type species Neolobatannularia liaoningensis Sun et Li sp. nov. from the Upper Triassic Yangcaogou Formation of Beipiao, Liaoning, China, is described in this paper. The new taxon is attributed to Equisetales of Sphenopsida based on its branch with internodes, node and leaves borne in whorls on nodes. It is a new member of the Mesozoic Sphenopsida. Although the new taxon shares some morphological characters with the genus Lobatannularia Kawasaki, a genus widely distributed in the Permian Cathaysia flora in East Asia, and the genus Lobatannulariopsis Yang from the Late Triassic of southwestern China, its unique branching pattern is markedly distinguished from the two known genera. Some Triassic known species of Lobatannularia may belong to the present new genus Neolobatannularia. | WANG Junyou LI Tao LIU Zhiping GUO Bin KANG Ai NA Yuling LI Yunfeng WANG Hongshan BO Junchen SUN Chunlin | 2019 | Global Geology2019，22，1： | 0 |
| 7 | Association Study between miR-181b rs322931 Polymorphism and Risk of Gastric Cancer显示文摘Objective:To explore the relationship between miR-181b rs322931 polymorphism and the risk of gastric cancer.Methods:The peripheral venous blood of 172 patients with gastric cancer and 224 healthy controls were collected.The miR-181b rs322931 was typed by TaqMan probe method,and correlation between miR-181b rs322931 and the risk of gastric cancer was evaluated using SPSS software.Results:The frequencies of miR-181b rs322931 CC,CT,TT genotype,C,and T allele were 61.6,33.7,4.7,78.5,and 21.5%in gastric cancer,and 74.1,23.7,2.2,85.9,and 14.1%in controls,respectively.After the%2 test and correction for age and gender,the risk of gastric cancer in carriers of CT and CT/TT genotypes increased by 1.71 and 1.79 times,respectively(CT vs.CC:95%CI,1.10-2.67,P=0.02;CT/TT compared with CC:95%CI,1.16-2.74,P=0.008).Moreover,compared with alleles,the risk of gastric cancer in T allele carriers increased by 1.69 times(95%CI,1.162.44,P=0.006).Conclusion:miR-181b rs322931 polymorphism may be one of the susceptibility genes of gastric cancer in the Chinese Han nationality. | Dingguo Pan Yunfeng Li Liang Ai Qi Zhang | 2021 | Journal of Clinical and Nursing Research2021，5，1： | 0 |
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