… Data-driven just-in-time learning based adaptive predictive control for blast furnace
Ironmaking. Control Theory & Applications, 2020, 37(2): 295-306 doi: 10.7641/CTA.2019.80689 …

人类利用视觉, 听觉等多种感官理解周围环境, 通过整合多种感知模态, 形成对事件的整体认识. 为
使机器更好地模仿人类的认知能力, 多模态认知计算模拟人类的“联觉”(synaesthesia), 探索图像…

… 如早期的基于 Boosting[21, 47] 的多核组合模型学习方法, 基于半 定规划(Semidefinite
programming, SDP)[41] 的多 核学习方法, 基于二次约束型二次规划(Quadratically constrained …

… A self-organizing recurrent fuzzy neural network based on multivariate time series analysis.
… -based adaptive neural control for nonlinear full-state constrained systems. IEEE Trans- …

… Abstract:To solve the unknown order of Hammerstein and multi innovation length constraint,a
sub-iteration updating multi innovation gradient identification algorithm was proposed. By …

… for improving the short-term prediction accuracy of wind power, promoting the development
of refined prediction technology, and ensuring the safe and stable operation of the system. …

: 智能空气动力学是人工智能与空气动力学的结合, 融入了第四研究范式(数据驱动) 的独特研究
方法, 已逐步发展成为一门独立的交叉学科. 本文首先对智能空气动力学的概念和内涵进行了剖析…

… process,the objective function and the constraint conditions,was mainly studied. The Beijing
… increment,and the constraint condition was improved at the same time. The results showed …

… status of forecasting methods, multi-level forecasting and adaptive forecasting systems in
existing … forecasting are summarized and prospected. Key words: deep learning; wind power …

… local consistent constraints (The dark region M denotes the convex global constraint, and
the combination of the light and dark regions L and M denotes the local consistent constraint.) …