With the modeling method, the paper gives the gray self -adaptive forecast model of the ground mobile target.
利用该建模方法，给出了地面运动目标轨迹的灰色自适应预测模型。
On the basis of this, a fuzzy-neural forecast controller is designed and robust adaptive control to the nonlinear big-lagged chaos system is realized.
在此基础上，又设计了模糊神经网络预测控制器，实现了对非线性、大时滞系统高精度的自适应控制。
The prediction model has very strong self-adaptability because of using adaptive fuzzy neural network based on Sugeno-Tanaka fuzzy model, and the forecast result is also satisfactory.
由于预测中使用了一种基于高木-关野模糊模型的自适应模糊神经网络，从而使预测模型具有很强的自适应能力，预测结果也比较令人满意。
The forecasting results of the case study has proved that the adaptive control exponential smoothing forecasting model suits water demand forecast in irrigation districts.
实例预报结果表明，把自适应指数平滑预报模型应用于灌区需水量预报中是可行的。
The adaptive particle swarm optimization is used to optimize the parameters of SVM so as to avoid artificial arbitrariness and enhance the forecast accuracy.
同时利用粒子群算法优化小波最小二乘支持向量机的参数，避免了人为选择参数的盲目性，从而提高了模型的预测精度。
The adaptive particle swarm optimization is used to optimize the parameters of SVM so as to avoid artificial arbitrariness and enhance the forecast accuracy.
同时利用粒子群算法优化小波最小二乘支持向量机的参数，避免了人为选择参数的盲目性，从而提高了模型的预测精度。
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