%0 Journal Article
%T Design and Noise Resistance Ability of Incremental Hybrid Multi-concepts Acquisition Algorithm<br>混合型多概念获取算法的设计及其抗噪音能力
%A LI Hong-bing
%A ZHOU Zhi-hua
%A CHEN Zhao-qian
%A <br>李红兵
%A 周志华
%A 陈兆乾
%J 软件学报
%D 1999
%I 
%X IHMCAP (incremental hybrid multi-concepts acquisition) algorithm combines the p robability based symbolic learning with neural learning. The balance of learning accuracy between the symbolic and the neural parts are proportioned successfull y, and the two different levels of thought are aboard laid by adhibiting FTART ( field theory-based adaptive resonance theory) neural network. A unique incremen tal learning mechanism is employed with this algorithm, which can adjust the fo rmer structure to improve learning accuracy by learning once instead of rebuildi ng the decision tree and the neural networks when the new examples are provided. It has higher speed, and is efficient. Moreover, the noisy sensibility of the s ystem is depressed by the incremental learning mechanism, which enables IHMCAP c an be applied to the tasks that require real-time online learning.
%K Hybrid model
%K incremental learning
%K neural network
%K noise disposal<br>混合模型
%K 增量学习
%K 神经网络
%K 噪音处理
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=7735F413D429542E610B3D6AC0D5EC59&aid=8022742AD9DDC4B0&yid=B914830F5B1D1078&vid=F3090AE9B60B7ED1&iid=94C357A881DFC066&sid=B99A53AADE50D922&eid=F204392B3B11C3BD&journal_id=1000-9825&journal_name=软件学报&referenced_num=1&reference_num=10