With the rapid development of science and technology, more and more new methods and technologies have been added to the traditional Chinese Medicine Inheritance model, which makes the process of inheritance of famous doctors have more means, and the results of inheritance are more objective, rigorous and intelligent. In the process of inheriting the informationization of famous doctors, there are some bottlenecks, such as data acquisition difficulties, data processing difficulties, algorithm application difficulties, analysis and summary difficulties. Integration of artificial intelligence with big data, deep learning algorithm and knowledge atlas technology has brought technological innovation to the informationization of famous doctors' inheritance. Under this wave, the team of the Intelligent Research and Development Center of Traditional Chinese Medicine, Institute of Traditional Chinese Medicine Information, Chinese Academy of Traditional Chinese Medical Sciences, has developed a series of professional application systems in the field of traditional Chinese medicine around the planning of famous doctors' inheritance and excavation, and has developed ancient Chinese medicine, such as Today's Medical Records Cloud Platform, Medical Records Big Data Analysis Platform, Cloud Medical Records APP, Famous Medical Heritage Workstation. To a certain extent, it can solve the problems of inefficient collection of medical records, lack of objective data support and information barriers in the summary of famous doctors' experience under the limitation of traditional model, so as to promote the inheritance of famous doctors' experience and enhance the teaching ability and efficiency of teachers and apprentices.
Circulating fluidized bed boiler, with heat storage capacity, nonlinear, large time delay, multi-variable and strong coupling characteristics, is a complex quantity control system. It is difficult to establish accurate model when the parameters of control object is uncertainty because of all disturbances. This article uses one way to identify model based on genetic algorithm and RBF network combined with generalized predictive control strategy, through online rolling optimization and feedback correction, to achieve predictive control. The results of the simulation show that it has strong robustness when the load condition changes, the parameter changes or lag affects.
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