公开(公告)号：US20120016824A1

公开(公告)日：2012-01-19

申请号：US13178722

申请日：2011-07-08

申请人： Mikhail Kalinkin ,  Bernhard Lang ,  Alexander Loginov

发明人： Mikhail Kalinkin ,  Bernhard Lang ,  Alexander Loginov

IPC分类号： G06F15/18

CPC分类号： G01M15/14 ,  G05B23/024

摘要： A method for computer-assisted analyzing of a technical system is provided. The technical system is described by a case base including multiple cases, each case including a state vector with a number of attributes, the state vector referring to an operation state of the technical system, wherein a class from a number of classes is assigned to each case, each class referring to an operation condition of the technical system. Each case is processed by extracting a local information vector depending on the classes of one or more neighboring cases in the case base, the neighboring cases being similar to the case being processed according to a neighborhood measure. Subsequently, machine learning of a classification is performed based on the extracted local information vectors of the cases in the case base, resulting in a learned adaptation function providing a class depending on a local information vector extracted for a case.

摘要翻译： 提供了一种用于计算机辅助分析技术系统的方法。 技术系统由包括多个情况的案例库描述，每个案例包括具有多个属性的状态向量，状态向量参考技术系统的操作状态，其中来自多个类的类被分配给每个 情况下，每个类都涉及技术系统的运行状况。 通过根据病例库中的一个或多个相邻病例的类别提取局部信息向量来处理每个病例，相邻病例与根据邻域测量被处理的病例相似。 随后，基于提取的案例库中的情况的本地信息向量来执行分类的机器学习，得到根据为案例提取的局部信息向量提供类的学习适应函数。