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This research mainly discusses the lethal factors of patients who receive the surgery of heart valve replacement for a long time. The research purpose is to provide the reference for the therapy of clinic. Logistic regressive mathematical model and a new conditioning (training) set are given. Applying incomplete difference analysis to the model and testing with reamer intercept method to ensure the...
A novel hybrid-genetic-algorithm process in multi-objective parallel mode (NHMGA), operated for tracking a 2-period-BP model-mapping, supported by optimally equipped Grid-computing framework, is proposed. This NHMGA is specially designed for personal on-line and real-time bio-information modeling which is successfully applied in soft-sensing of blood-glucose. The related application example and its...
In many realistic applications, process noise is known to be neither white nor normally distributed. When identifying models in these cases, it may be more effective to minimize a different penalty function than the standard sum of squared errors (as in a least-squares identification method). This paper investigates model identification based on two different penalty functions: the 1-norm of the prediction...
This paper will use fuzzy integral to structure the diagnostic model of gestational diabetes mellitus. The Sugeno measure is obtained by training of BP neural network. The BP neural network is easy to get into local optimum, so the algorithm of simulated annealing is used to optimize the BP neural network, and it will obtain an approximate global optimal solution. In this diagnostic model, there are...
The pre-diagnosis to type 2 diabetes, and the effective prophylaxis and treatment of its complication is to be worthy paying attention to. So an intelligent diagnosis based on quantum particle swarm optimization (QPSO) algorithm and weighted least squares support vector machines (WLS-SVM) is presented, which can overcome the disadvantage of large sample data, slow model-building and rather large deviation...
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