由于预先运用基于FCM的自适应模糊聚类方法确定模糊神经元网络合理的结构，并设置网络的初始权值，从而可提高网络的训练速度。
Since an FCM based self adaptive fuzzy clustering technique is employed to determine the proper structure of the FNN and set the initial weights in advance, the network can be trained rapidly.
使用减法聚类和自适应模糊神经网络方法设计了一种水下机器人运动规划器。
By using the methods of subtraction clustering and adaptive fuzzy neural network, a sort of motion planner for the underwater vehicle was designed.
采用自适应门限进行阈值分割，得到二值化的图像；利用聚类的方法去掉噪声点。
Binaryzation image is obtained through adaptive threshold segmentation and noise is removed by sorting method.
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