表 3：模型参数估计结果（Model Parameter Estimates） COMEX(-1) COMEX(-2) COMEX(-3) COMEX(-4) COMEX(-5) COMEX(-6) COMEX(-7) USDX(-1) USDX(-2) USDX(-3) USDX(-4) USDX(-5) USDX...
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仿真结果表明了该线性时变模型和参数估计算法的可行性，表明该自适应预测控制方法具有优良的控制品质。
Simulation results demonstrate the feasibility of the model and the parameter estimation algorithm, and show that the adaptive predictive control method has excellent control quality.
实验结果表明，该算法是一种有效的系统模型参数估计方法。
The experiment results show that particles swarm optimization is an effective method for parameter estimation of system model.
采用零截尾计数模型分析，不仅可以解决零截尾计数分布问题，且参数估计结果更准确，拟合效果更合理。
Zero-truncated count model could not only solve the issue of zero-truncated count distribution, but also the parameter estimates were more accurate, the fitting results were more reasonable.
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