Eco-friendly approach for preparation of hybrid silica aerogel via freeze drying method

Journal of Materials Science - In this paper, an eco-friendly method of producing hybrid silica aerogels by freeze-drying method (FD) is proposed. In the freeze-drying system, deionized water was...     

A Pattern Recognition Method of Personalized Adaptive Learning in Online Education

Mobile Networks and Applications - In order to effectively identify the pattern of personalized adaptive learning in online education and improve the recommendation satisfaction of personalized...     

Multi-UAV Collaborative Wireless Communication Networks for Single Cell Edge Users

Mobile Networks and Applications - Due to fast deployment, strong survivability and flexible scheduling, multiple unmanned aerial vehicles (UAV) can synergistically optimize the trajectory and...     

基于大数据深度学习的输电塔结构抗风易损性评估

为了有效预测输电网系统在强风作用下的响应，并开展高效精准的性能评估，文章提出了基于深度学习模型的风致易损性评估框架。以某具备健康监测系统的输电塔结构为例，首先对监测数据进行清洗和重构，通过大数据深度学习建立荷载输入和响应输出的等效映射模型，然后通过数值模拟生成灾害强度均匀的风场数据并由深度学习模型预测输电塔关键杆件响应，计算不同性能水准的易损性曲线。研究结果表明，经训练的深度学习模型可以涵盖实际工程中存在的各类不确定性因素，有效映射复杂风环境下输电塔结构的动力响应。提出的框架方法可以避免单纯通过数值模型制备大量动态响应数据，更高效地进行输电网系统风致易损性评估。