知识管理自学习案例活性测度与学习阈控

KML-Case Activity Measure and Learning Threshold Control

文章从应用价值、环境适应与资源稀缺视角对自学习案例(KML-Case)活性内涵进行了剖析,从6个方面系统地分析了KML-Case活性测度的实施意义。在此基础上,分析、设计并提出了环境适应与资源稀缺视角下的KMLCase活性测度方法与实现策略,通过算例演示了环境适应视角下的KML-Case活性测度过程。基于KML-Case活性测度结果,阐释了KML-Case学习阈控的基本内涵,分析了KMS待存储KML-Case与待进化KML-Case的阈控方法与策略。

The paper analyzes the connotation of KML-Case activity from the perspective of application value, environmental adaptation and resources scarcity, and systematically analyzes the implementation significance of KML-Case activity measure from 6 aspects. On this basis, KML-Case activity measuring methods and implementing strategies are analyzed, designed and proposed from the perspective of environmental adaptation and resources scarcity. And the KML-Case activity measuring process is demonstra- ted by a numerical example from the perspective of environmental adaptation. Based on the measuring results of KML-Case activity, the basic connotation of KML-Case learning threshold control is further explained, and the threshold control methods and strategies for the KML-Case to be stored and evolved are analyzed.