3篇
您的检索式：作者名="SONG Wanping"
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| 1 | Reinforcement learning based parameter optimization of active disturbance rejection control for autonomous underwater vehicle显示文摘This paper proposes a liner active disturbance rejection control(LADRC) method based on the Q-Learning algorithm of reinforcement learning(RL) to control the six-degree-of-freedom motion of an autonomous underwater vehicle(AUV).The number of controllers is increased to realize AUV motion decoupling.At the same time, in order to avoid the oversize of the algorithm, combined with the controlled content, a simplified Q-learning algorithm is constructed to realize the parameter adaptation of the LADRC controller.Finally, through the simulation experiment of the controller with fixed parameters and the controller based on the Q-learning algorithm, the rationality of the simplified algorithm, the effectiveness of parameter adaptation, and the unique advantages of the LADRC controller are verified. | SONG Wanping CHEN Zengqiang SUN Mingwei SUN Qinglin | 2022 | Journal of Systems Engineering and Electronics2022，33，1： | 1 |
| 2 | Recognition for avian influenza virus proteins based on support vector machine and linear discriminant analysis显示文摘Total 200 properties related to structural characteristics were employed to represent structures of 400 HA coded proteins of influenza virus as training samples. Some recognition models for HA proteins of avian influenza virus (AIV) were developed using support vector machine (SVM) and linear discriminant analysis (LDA). The results obtained from LDA are as follows: the identification accuracy (Ria) for training samples is 99.8% and Ria by leave one out cross validation is 99.5%. Both Ria of 99.8% for training samples and Ria of 99.3% by leave one out cross validation are obtained using SVM model, respectively. External 200 HA proteins of influenza virus were used to validate the external predictive power of the resulting model. The external Ria for them is 95.5% by LDA and 96.5% by SVM, respectively, which shows that HA proteins of AIVs are preferably recognized by SVM and LDA, and the performances by SVM are superior to those by LDA. | LIANG GuiZhao CHEN ZeCong YANG ShanBin MEI Hu ZHOU Yuan YANG Li ZHOU Peng YANG ShengXi SHU Mao LIAO ChunYang WU ShiRong LI GenRong HE Liu GAO JianKun Gan MengYu LI DeJing CHEN GuoPing WANG GuiXue LONG Sha JING JuHua ZHENG XiaoLin ZENG Hui ZHANG QiaoXia ZHANG MengJun YANG Qi TIAN FeiFei TONG JianBo WANG JiaoNa LIU YongHong LI Bo QIU LiangJia CAI ShaoXi ZHAO Na YANG Yan SU XiaLi SONG Jian CHEN MeiXia ZHANG XueJiao SUN JiaYing LI JingWei CHEN GuoHua CHEN Gang DENG Jie PENG ChuanYou ZHU WanPing XU LuoNan WU YuQuan LIAO LiMin LI Zhi LI Jun LU DaJun SU QinLiang HUANG ZhengHu ZHOU Ping LI ZhiLiang | 2008 | Science China Chemistry2008，51，2： | 0 |
| 3 | Preparation and Characterization of Nanostructured Lipid Carrier Loaded with UVA/UVB Filters显示文摘A new photoprotective system based on encapsulating UVA (butyl methoxydibenzoylmethane, BMBM) and UVB (octyl methoxycinnamate, OMC) filters into nanostructured lipid carriers (NLC) has been prepared to develop cosmetic formulations with effective UV protection. BMBM/OMC-loaded NLC was prepared by ultrasonication-homogenisation, and analysed by particle size, zeta potential (ZP), encapsulation efficiency (EE), scanning electron microscopy (SEM), fourier transform infrared spectroscopy (FTIR) and differential scanning calorimetry (DSC). Moreover, the UV protection property and photostability were investigated and compared with BMBM/OMC-conventional emulsions. The particle size and ZP of BMBM/OMC-loaded NLC were 310.24 nm and -33.6 mV, EE of BMBM and OMC were 85.46% and 99.32%. SEM, FTIR and DSC analysis confirmed BMBM and OMC entrapped in the lipid matrix core and the structure was stable during storage. Compared with conventional emulsion, BMBM/OMC-loaded NLC displayed perfect photo protection property in whole UV range. The photostability studies showed that the NLC can improve the photostability of sunscreens. | Zhang Qianjie Zhao Xiaowei Song Lili Ou Wenhua Zhang WanPing Zhu Haiyang | 2018 | China Detergent & Cosmetics2018，3，4： | 0 |
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