余传锦
副教授
个人信息Personal Information
学历:博士研究生毕业
学位:工学博士学位
办公地点:西南交通大学土木馆#1523
性别:男
在职信息:在岗
毕业院校:西南交通大学
所在单位:土木工程学院
报考该导师研究生的方式
欢迎你报考余传锦老师的研究生,报考有以下方式:
1、参加西南交通大学暑期夏令营活动,提交导师意向时,选择余传锦老师,你的所有申请信息将发送给余传锦老师,老师看到后将和你取得联系,点击此处参加夏令营活动
2、如果你能获得所在学校的推免生资格,欢迎通过推免方式申请余传锦老师研究生,可以通过系统的推免生预报名系统提交申请,并选择意向导师为余传锦老师,老师看到信息后将和你取得联系,点击此处推免生预报名
3、参加全国硕士研究生统一招生考试报考余传锦老师招收的专业和方向,进入复试后提交导师意向时选择余传锦老师。
4、如果你有兴趣攻读余传锦老师博士研究生,可以通过申请考核或者统一招考等方式报考该导师博士研究生。
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- Yu, C., Li, Y., Xiang, H., Zhang, M., 2018b. Data mining-assisted short-term wind speed forecasting by wavelet packet decomposition and Elman neural network. J. Wind Eng. Ind. Aerodyn. 175, 136–143. https://doi.org/10.1016/j.jweia.2018.01.020
- Yu, C., Xiang, H., Li, Y., Pan, M., 2018c. Optimization of longitudinal viscous dampers for a freight railway cable-stayed bridge under braking forces. Smart Struct. Syst. 21, 669–675. https://doi.org/10.12989/sss.2018.21.5.669
- Yu, C., Li, Y., Zhang, M., 2017a. Comparative study on three new hybrid models using Elman Neural Network and Empirical Mode Decomposition based technologies improved by Singular Spectrum Analysis for hour-ahead wind speed forecasting. Energy Convers. Manag. 147, 75–85. https://doi.org/10.1016/j.enconman.2017.05.008
- Chen, Q., Yu, C., Li, Y., 2022a. General strategies for modeling joint probability density function of wind speed, wind direction and wind attack angle. J. Wind Eng. Ind. Aerodyn. 225, 104985. https://doi.org/10.1016/j.jweia.2022.104985
- Chen, Q., Yu, C., Li, Y., Zhang, X., He, P., 2022b. Directional wind characteristics analysis in the mountainous area based on field measurement. J. Wind Eng. Ind. Aerodyn. 229, 105162. https://doi.org/10.1016/j.jweia.2022.105162
- Yu, C., Li, Y., Zhang, M., 2017b. An improved Wavelet Transform using Singular Spectrum Analysis for wind speed forecasting based on Elman Neural Network. Energy Convers. Manag. 148, 895–904. https://doi.org/10.1016/j.enconman.2017.05.063
- Yu, C., Li, Y., Bao, Y., Tang, H., Zhai, G., 2018a. A novel framework for wind speed prediction based on recurrent neural networks and support vector machine. Energy Convers. Manag. 178, 137–145. https://doi.org/10.1016/j.enconman.2018.10.008
- Yu, C., Li, Y., Chen, Q., He, J., Zhao, L., 2022. An advanced particle swarm optimization algorithm and its application to search flutter critical velocity of bridges. Adv. Struct. Eng. 136943322210926. https://doi.org/10.1177/13694332221092670
- Yu, C., Li, Y., Zhang, M., Zhang, Y., Zhai, G., 2019. Wind characteristics along a bridge catwalk in a deep-cutting gorge from field measurements. J. Wind Eng. Ind. Aerodyn. 186, 94–104. https://doi.org/10.1016/j.jweia.2018.12.022
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