Bone tumor is a common bone disease , its category includes benign tumor , malignant tumor , metastasis tumor , cancroid pathological changes , and etc . , it ' s usually seen in juvenile and does many harms 骨肿瘤是一种常见的骨科疾病，有良性、恶性、转移癌及癌样病变等，多发于青少年，危害较大。
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This paper adopts an adaptive learning algorithm based on hierarchy clustering to update user profile , which continuously abstract the cancroids of one class of optimum information from the feedback flow of system , which effectively shield the learning process from plenty of feedback noises produced by distorted threshold and sparseness of initial information , which also can imitate artificial feedback approximately to perfect the intelligence of adaptive learning mechanism 摘要本文采用一种基于层次聚类的自适应学习策略，从系统反馈的信息流中，动态提取一类最优信息的质心更新用户模型，有效屏蔽了阈值失真和初始信息稀疏造成的大量反馈噪声，并且能够近似模仿人工反馈，完善自适应学习机制的智能性。
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In accordance with the problem that the fcm algorithm is quite time - consuming for search out cluster cancroids and may not be suitable for on - line modeling and control . this dissertation proposed an improved fuzzy identification method based multistage random sampling fuzzy c - means clustering algorithm ( mrfcm ) . it has higher approximate precision and the cpu time has slowed down sharply compared with the common fuzzy Johnyen和liangwang介绍了几种应用于模糊模型的信息优化准则，本论文在此基础上对统计信息准则进行一些改进，并与快速模糊聚类和正交最小二乘方法结合，提高了模型的辨识精度和泛化能力。
