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Simultaneous optimization and control for polypropylene grade transition with two-layer hierarchical structure 被引量:2
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作者 娄海川 苏宏业 +3 位作者 古勇 谢磊 荣冈 侯卫锋 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2015年第12期2053-2064,共12页
In this paper,a two-layer hierarchical structure of optimization and control for polypropylene grade transition was raised to overcome process uncertain disturbances that led to the large deviation between the open-lo... In this paper,a two-layer hierarchical structure of optimization and control for polypropylene grade transition was raised to overcome process uncertain disturbances that led to the large deviation between the open-loop reference trajectory and the actual process.In the upper layer,the variant time scale based control vector parametric methods(VTS-CVP) was used for dynamic optimization of transition reference trajectory,while nonlinear model predictive controller(NMPC) based on closed-loop subspace and piece-wise linear(SSARX-PWL) model in the lower layer was tracking to the reference trajectory from the upper layer for overcoming high-frequency disturbances.Besides,mechanism about trajectory deviation detection and optimal trajectory updating online were introduced to ensure a smooth transition for the entire process.The proposed method was validated with the real data from an industrial double-loop propylene polymerization reaction process with developed dynamic mechanism mathematical model. 展开更多
关键词 Polypropylene grade transition Two-layer hierarchical structure Deviation detection
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ICPS multi-target constrained comprehensive security control based on DoS attacks energy grading detection and compensation
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作者 HAN Yinlong HAN Xiaowu 《Journal of Measurement Science and Instrumentation》 CAS CSCD 2024年第4期518-531,共14页
Aiming at the industry cyber-physical system(ICPS)where Denial-of-Service(DoS)attacks and actuator failure coexist,the integrated security control problem of ICPS under multi-objective constraints was studied.First,fr... Aiming at the industry cyber-physical system(ICPS)where Denial-of-Service(DoS)attacks and actuator failure coexist,the integrated security control problem of ICPS under multi-objective constraints was studied.First,from the perspective of the defender,according to the differential impact of the system under DoS attacks of different energies,the DoS attacks energy grading detection standard was formulated,and the ICPS comprehensive security control framework was constructed.Secondly,a security transmission strategy based on event triggering was designed.Under the DoS attack energy classification detection mechanism,for large-energy attacks,the method based on time series analysis was considered to predict and compensate for lost data.Therefore,on the basis of passive and elastic response to small energy attacks,the active defense capability against DoS attacks was increased.Then by introducing the conecomplement linearization algorithm,the calculation methods of the state and fault estimation observer and the integrated safety controller were deduced,the goal of DoS attack active and passive hybrid intrusion tolerance and actuator failure active fault tolerance were realized.Finally,a simulation example of a four-capacity water tank system was given to verify the validity of the obtained conclusions. 展开更多
关键词 industry cyber-physical system(ICPS) Denial-of-Service(DoS)attacks energy grading detection security event triggering mechanism time series analysis methods cone complementary linearization
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The application research on the Automatic Detection and Grading of Microaneurysms in Fundus Images of Diabetic Retinopathy by Artificial Intelligence Deep Learning Algorithms
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作者 Zhao Xiaomin 《Modern General Practice》 2024年第1期35-39,共5页
This research focuses on the automatic detection and grading of microaneurysms in fundus images of diabetic retinopathy using artificial intelligence deep learning algorithms.By integrating multi-source fundus image d... This research focuses on the automatic detection and grading of microaneurysms in fundus images of diabetic retinopathy using artificial intelligence deep learning algorithms.By integrating multi-source fundus image data and undergoing a rigorous preprocessing workflow,a hybrid deep learning model architecture combining a modified U-Net and a residual neural network was adopted for the study.The experimental results show that the model achieved an accuracy of[X]%in microaneurysm detection,with a recall rate of[Y]%and a precision rate of[Z]%.In terms of grading diabetic retinopathy,the Cohen’s kappa coefficient for agreement with clinical grading was[K],and there were specific sensitivities and specificities for each grade.Compared with traditional methods,this model has significant advantages in processing speed and result consistency.However,it also has limitations such as insufficient data diversity,difficulties for the algorithm in detecting microaneurysms in severely hemorrhagic images,and high computational costs.The results of this research are of great significance for the early screening and clinical diagnosis decision support of diabetic retinopathy.In the future,it is necessary to further optimize the data and algorithms and promote clinical integration and telemedicine applications. 展开更多
关键词 Diabetic retinopathy MICROANEURYSMS Deep learning Fundus images Automatic detection and grading
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