An adaptive fuzzy clustering identification algorithm is employed to get the T-S fuzzy model of a system.
用基于T - S模型的自适应模糊聚类辨识算法对系统进行辨识。
Color clustering is used to segment the fabric image, and a new algorithm of warp yarn segmentation is proposed to perform the identification more precisely.
为了提高单层组织自动识别的精度，运用颜色聚类等方法分割织物样图，并提出了一种经纱分割算法，实现了经纬纱线的准确分割。
A new coin identification method based on ant colony algorithm with clustering characteristics is proposed in this paper.
利用蚁群算法的聚类能力，提出一种硬币识别新方法。
The system identifier based on RBF neural network which applies nearest neighbor clustering algorithm realizes the identification of the inverse dynamic system model.
辨识器采用RBF神经网络结构和最近邻聚类算法，实现了对系统逆动力学模型的动态辨识。
In the part of traffic congestion identification technology, we improved the traditional fuzzy clustering algorithm.
在交通拥堵判别算法方面，改进了传统的基于模糊综合判别的交通拥堵判别模型。
In the part of traffic congestion identification technology, we improved the traditional fuzzy clustering algorithm.
在交通拥堵判别算法方面，改进了传统的基于模糊综合判别的交通拥堵判别模型。
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