Tuberculosis (TB) affects people globally and is being reconsidered as a serious public health problem in China. Reliable forecasting is useful for the prevention and control of TB. This study proposes a hybrid model combining autoregressive integrated moving average (ARIMA) with a nonlinear autoregressive (NAR) neural network for forecasting the incidence of TB from January 2007 to March 2016. Prediction performance was compared between the hybrid model and the ARIMA model. The best-fit hybrid model was combined with an ARIMA (3,1,0) × (0,1,1)12 and NAR neural network with four delays and 12 neurons in the hidden layer. The ARIMA-NAR hybrid model, which exhibited lower mean square error, mean absolute error, and mean absolute percentage error of 0·2209, 0·1373, and 0·0406, respectively, in the modelling performance, could produce more accurate forecasting of TB incidence compared to the ARIMA model. This study shows that developing and applying the ARIMA-NAR hybrid model is an effective method to fit the linear and nonlinear patterns of time-series data, and this model could be helpful in the prevention and control of TB.
To satisfy the strict requirements of dynamic pressure for air-breathing hypersonic vehicle during the initiation, a dynamic pressure control method based on the model reference sliding mode theory is designed. Firstly, the motion equation of the air-breathing hypersonic vehicle is built, and the dynamic pressure linearization model is established by the small perturbation method. Secondly, the control system, designed by the model reference sliding mode control theory, can quickly track the reference model. Finally, the six degrees of freedom simulation model is built and used for digital simulation. The simulation results show that the designed control system can accurately track the dynamic pressure command with great robustness.
The dynamic characteristics of the cable hoisting system (CHS) are studied by combining theoretical modelling and visual simulation. The dynamic model is derived using D’Alembert’s principle. It contains the effect of horizontal motion and lifting motion, and also takes into account the quality of the cable to improve the accuracy of model. The Runge-Kutta method is used to solve model numerically, and simulation is conducted within Adams environment to verify the dynamic model. Based on the dynamic model and numerical calculation, the effect of horizontal motion, lifting motion and system parameters on swing was studied. The results show that the dynamic model and numerical calculations are accurate; during the movement, the payload oscillation is mainly affected by the initial acceleration, sudden change of acceleration and lifting speed; the length of steel cable and the mass of hoisting payload determine the frequency of CHS, which does not affect the payload oscillation; the oscillation and frequency are affected by lifting laws; and the study of acceleration laws can be used to guide the design and control of CHS.
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