This paper addresses the important intelligent predicting problem of peritoneal absorption rate in the peritoneal dialysis treatment process of renal failure. As the index of dialysis adequacy, KT/V and Ccr are widely...This paper addresses the important intelligent predicting problem of peritoneal absorption rate in the peritoneal dialysis treatment process of renal failure. As the index of dialysis adequacy, KT/V and Ccr are widely used and accepted. However, growing evidence suggests that the fluid balance may play a critical role in dialysis adequacy and patient outcome. Peritoneal fluid absorption decreases the peritoneal fluid removal. Understanding the peritoneal fluid absorption rate will help clinicians to optimize the dialysis dwell time. The neural network approach is applied to the prediction of peritoneal absorption rate. Compared with multivariable regression method, the experimental results showed that neural network method has an advantage over multivariable regression. The application of this predicting method based-on neural network in clinic is instructive. Keywords Peritoneal dialysis - Neural network - Intelligent prediction - Peritoneal absorption This work was supported in part by the guangdong Province Scientific and Technological key Research Program (No.2002C3021l) and the South China University of Technology.展开更多
Based on the quadratic supply rate, the problem of robust dissipative control for a class of uncertain nonlinear system with sector nonlinear input is discussed. The uncertainty is described by bounded norm. It is sho...Based on the quadratic supply rate, the problem of robust dissipative control for a class of uncertain nonlinear system with sector nonlinear input is discussed. The uncertainty is described by bounded norm. It is shown that the robust dissipative control problem can be resolved for all admissible uncertainty, if there exists a storage function such that Hamilton Jacobi inequality holds. When the uncertainties of the system satisfy the matching condition, and input function within the boundedness of the sector, the closed loop system will be stronger dissipativeness, and the controller which we obtained in the paper is more flexible, because it contains an adjustable parameter for some certain range.展开更多
文摘This paper addresses the important intelligent predicting problem of peritoneal absorption rate in the peritoneal dialysis treatment process of renal failure. As the index of dialysis adequacy, KT/V and Ccr are widely used and accepted. However, growing evidence suggests that the fluid balance may play a critical role in dialysis adequacy and patient outcome. Peritoneal fluid absorption decreases the peritoneal fluid removal. Understanding the peritoneal fluid absorption rate will help clinicians to optimize the dialysis dwell time. The neural network approach is applied to the prediction of peritoneal absorption rate. Compared with multivariable regression method, the experimental results showed that neural network method has an advantage over multivariable regression. The application of this predicting method based-on neural network in clinic is instructive. Keywords Peritoneal dialysis - Neural network - Intelligent prediction - Peritoneal absorption This work was supported in part by the guangdong Province Scientific and Technological key Research Program (No.2002C3021l) and the South China University of Technology.
基金the National Natural Science Foundation of China(6987401569934030)and Foundation of the Education Department of Hubei Province(99A121)
文摘Based on the quadratic supply rate, the problem of robust dissipative control for a class of uncertain nonlinear system with sector nonlinear input is discussed. The uncertainty is described by bounded norm. It is shown that the robust dissipative control problem can be resolved for all admissible uncertainty, if there exists a storage function such that Hamilton Jacobi inequality holds. When the uncertainties of the system satisfy the matching condition, and input function within the boundedness of the sector, the closed loop system will be stronger dissipativeness, and the controller which we obtained in the paper is more flexible, because it contains an adjustable parameter for some certain range.
