导师信息部分2:
获奖情况
1、 获得2021年度“甘肃省教学成果奖二等奖”,获奖人:摆玉龙,范满红,黄羿博等2、 获得2019年甘肃省高校创新创业教学团队;3、 指导学生获得2019全国大学生电子设计大赛甘肃赛区二等奖;4、 指导学生获得2019全国大学生电子设计大赛甘肃赛区一等奖;5、 指导学生获得甘肃省第十二届挑战杯全国大学生课外学术作品三等奖;6、 主讲的《走进电世界》获2018年度甘肃省精品资源共享课;7、 获得2017年甘肃省创新创业慕课《STEAM创新创业讲坛》;8、 指导学生获得2017年全国大学生电子设计大赛国家二等奖1项;9、 主讲的《自动控制原理》获2015年度甘肃省精品资源共享课;10、获得2015年甘肃省高校科研优秀成果奖技术发明奖三等奖,获奖人:摆玉龙,陈毅,庄志强等;11、获得2013年度“甘肃省教学成果奖教育厅级奖”,获奖人:摆玉龙,马永杰,何新征,陈辉,严春满;12、获得2012年度“甘肃省第一届青年教师讲课比赛(工科组)”,第五名(三等奖);13、指导学生获得2011年中国机器人大赛“轻量级机器人游中国”全国一等奖;14、指导学生获得2011年全国大学生电子设计大赛国家二等奖;15、获得2010年度西北师范大学“优秀班主任”;16、获得2010年度西北师范大学“社会实践优秀指导教师;17、主讲的《自动控制原理课程》获2010年度校级双语示范课程;18、获得2009年度“甘肃省教学成果奖教育厅级奖”,获奖人:摆玉龙,马永杰,赵兴虎,马胜前;19、指导学生获得2009年全国电子专业人才设计与技能大赛国家三等奖;20、获得2009年度西北师范大学“优秀实习指导教师”;21、获得2008年度西北师范大学“教学质量优秀教师奖”;22、获得2007年度“甘肃省教学成果奖二等奖”,获奖人:杨志民,马永杰,摆玉龙,马胜前;23、获得2004年“荷兰政府惠更斯(Huygens)奖学金”;24、获得2003年“日本政府JICA奖学金”;25、指导学生获得第四届全国大学生“飞思卡尔”智能汽车竞赛全国总决赛二等奖;26、指导学生获得第11届挑战杯甘肃省一等奖1项;27、获得中国电子教育学会“十二•五”教育科学研究课题国家二等奖;
发表论文目录
主要的代表性论文有:[1] YuLong Bai*(摆玉龙), Ming-De Liu, Lin Ding, Yong-Jie Ma. Double-layer staged training echo-state networks for wind speed prediction using variational mode decomposition. Applied Energy, 2021, 301(OCT.15):117461. (1区,Top期刊,IF9.746)[2] Lin Ding, Yulong Bai*(摆玉龙), Ming-De Liu, Man-Hong Fan, Jie Yang, Predicting short wind speed with a hybrid model based on a piecewise error correction method and Elman neural network. Energy, 2022, Volume 244, Part A, 122630. (1区,Top期刊,IF7.147)[3] LiHong Tang, YuLong Bai*(摆玉龙), JieYang, YaNi Lu. A hybrid prediction method based on empirical mode decomposition and multiple model fusion for chaotic time series. Chaos, Solitons and Fractals:Nonlinear Science, and Nonequilibrium and Complex Phenomena, 2020,141. (数学1区),Top期刊,IF5.944[4] MingDe Liu, Lin Ding, YuLong Bai*(摆玉龙). Application of hybrid model based on empirical mode decomposition, novel recurrent neural networks and the ARIMA to wind speed prediction. Energy Conversion and Management, 2021, 113917. (1区,Top期刊,IF9.709[5] Yu-ting Huang, Yu-long Bai, Lin Ding, Ya-Jie Zhu & Yong-Jie Ma,Application of a Hybrid Model Based on ICEEMDAN, Bayesian Hyperparameter Optimization GRU and the ARIMA in Nonferrous Metal Price Prediction[J]. Cybernetics and Systems, 2022: 1-33.[6] Xiaofeng Li, Yulong Bai, Weishuan Pan, Di Wang, Yong-Jie Ma, Development of a Family of Chaotic Systems with Infinite Equilibria and Its Application for Image Encryption[J]. Complexity, 2022, 2022.[7] Wen Yan Xing, Yu Long Bai, Lin Ding, Qing He Yu, Wei Song; Application of a hybrid model based on GA–ELMAN neural networks and VMD double processing in water level prediction,Journal of Hydroinformatics 2022,2022.016.[8] Lin Ding, Yulong Bai , Ming-De Liu, Predicting short wind speed with a hybrid model based on a piecewise error correction method and Elman neural network. Energy.2021.[9] YuLong Bai*(摆玉龙), Di Wang, Yizhao Wang, Mingheng Chang. Differential Evolution Algorithm-based Multiple-factor Optimization Methods for Data Assimilation. Intelligent Data Analysis, 2021: 1473 – 1486.[10] Manhong Fan, YuLong Bai*(摆玉龙), Lili Wang, Lin Ding. Combining a Fully Connected Neural Network With an Ensemble Kalman Filter to Emulate a Dynamic Model in Data Assimilation, IEEE Access, vol. 9, pp. 144952-144964, 2021, doi: 10.1109/ACCESS.2021.3120482.[11] Manhong Fan, YuLong Bai*(摆玉龙), Liliwang Wang, Lihong Tang, Lin Ding. Coupling theK-nearest neighbors and locally weighted linear regression with ensemble Kalman filter for data-driven data assimilation. Open Geosciences, 2021, 13(1):1395-1413.[12] Yu-long Bai*,Ming-de Liu, Lin Ding, Yongjie Ma. Double-layer staged training echo-state networks for wind speed prediction using variational mode decomposition [J]. Applied Energy, 2021, 301,117461. (SCI)[13] Ming-de Liu, Lin Ding, Yu-long Bai*. Application of hybrid model based on empirical mode decomposition, novel recurrent neural networks and the ARIMA to wind speed prediction[J]. Energy Conversion and Management, 2021,233,113017. (SCI)[14] Yani Lu, Yu Long Bai*, Lihong Tang, Wendi Wan and Yongjie Ma. Secondary factor induced wind speed time-series prediction using self-adaptive interval type-2 fuzzy sets with error correction[J]. Energy Reports,2021.(SCI)[15] J K Duan, Y L Bai*, Q Wei and M H Fan. Super rogue waves in coupled electric transmission lines[J]. Indian Journal of Physics,2020.(SCI)[16] Lihong Tang, Yu Long Bai*. A hybrid prediction method based on empirical mode decomposition and multiple model fusion for chaotic time series[J]. Chaos, Solitons and Fractals,2020.(SCI)[17] Yu Long Bai*, Lihong Tang, Man Hong Fan, Xiao yan Ma and Yang Yang. Fuzzy First‐Order Transition‐Rules‐Trained Hybrid Forecasting System for Short‐Term Wind Speed Forecasts[J]. Energies,2020.(SCI)[18] Yu Long Bai*, Xiao yan Ma and Lin Ding. A Fuzzy-Logic-Based Covariance Localization Method in Data Assimilation[J]. Atmosphere,2020.(SCI)[19] Jikai Duan, Hongchao Zuo*, Yulong Bai, Jizheng Duan, Mingheng Chang, Bolong Chen. Short-term wind speed forecasting using recurrent neural networks with error correction[J]. Energy, 2021.(SCI