In this paper, a hybrid multi-concept acquisition system HMCAS is proposed. HMCAS can perform incremental supervised learning on arbitrary sequences composed of analog or binary inputs. The kernel algorithm of HMCAS, named HMCAP, which integrates symbolic and neural learning based on the probability of instance space, has the ability of generating concept descriptions in the form of hybrid decision tree. The prototype system of HMCAS has been applied to the field of typhoon forecasting and achieved successful result.%文章实现混合型多概念获取系统HMCAS(hybrid multi-concept acquisition system).无论在离散值或连续值输入下,HMCAS系统都可以实现增量式教师学习.HMCAS的核心算法HMCAP基于事例空间的概率分布,结合了符号学习和神经网络学习,能够以混合型判定树形式产生概念描述.HMCAS的原型系统已经成功应用于台风预测领域.
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