结果表明，用高木-关野模糊系统得到的结果比通常用的BP网络要好。
The results obtained by using Takagi-Sugeno fuzzy system were better than those by commonly used BP-networks.
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 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.
不同于其他动力定位船舶模糊控制器设计，本文采用基于高木—关野模糊逻辑系统的方法设计模糊控制器。
Unlike other traditional design method of ship dynamic positioning fuzzy controller. This paper use Tagaki-Sugeno fuzzy logic system to design the fuzzy controller.
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