A process experimental platform is designed and developed for complex process industrial modeling and control.
为方便对复杂工业过程的建模与控制研究，开发了过程实验平台。
Considering the complexity and the time variability of industrial process, an adaptive Supervised Distributed Neural Networks (SDNN) is proposed for modeling of industrial process.
针对工业生产过程的复杂性和时变性，提出一种用于工业生产过程建模的自适应监督式分布神经网络(SDNN)。
A modeling and identification platform for industrial process is introduced, including its design and implementation.
提出了一种面向工业过程的可视化建模辨识平台的设计和实现方法。
Calculation results revealed the relationship between operation parameters and SMB performances, which were beneficial to the optimization and the modeling of the industrial process.
通过对分子筛脱蜡过程的模拟计算，揭示了操作参数和过程性能之间的关系，这对于过程优化、工艺设计和操作具有重要指导意义。
A novel fluid network model of chemical industrial process is proposed for the modeling in training simulators. It's a fluid network model with temperature and composition change.
建立了化工过程仿真培训系统建模中的流体网络模型，这是有温度和组分变化的流体网络模型。
It adjusts the traditional research findings and applys the findings to the control modeling of complex industrial process.
对传统分析结果进行了校正，并将研究结果应用在针对复杂大生产过程的控制模型。
It adjusts the traditional research findings and applys the findings to the control modeling of complex industrial process.
对传统分析结果进行了校正，并将研究结果应用在针对复杂大生产过程的控制模型。
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