Invention Grant
US09256224B2 Method of sequential kernel regression modeling for forecasting and prognostics
有权
用于预测和预测的序列内核回归模型的方法
- Patent Title: Method of sequential kernel regression modeling for forecasting and prognostics
- Patent Title (中): 用于预测和预测的序列内核回归模型的方法
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Application No.: US13186200Application Date: 2011-07-19
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Publication No.: US09256224B2Publication Date: 2016-02-09
- Inventor: James P. Herzog
- Applicant: James P. Herzog
- Applicant Address: US VA Charlottesville
- Assignee: GE INTELLIGENT PLATFORMS, INC
- Current Assignee: GE INTELLIGENT PLATFORMS, INC
- Current Assignee Address: US VA Charlottesville
- Agency: GE Global Patent Operation
- Main IPC: G06N7/00
- IPC: G06N7/00 ; G05B23/02 ; G06K9/62

Abstract:
A method for determining the future operational condition of an object includes obtaining reference data that indicates the normal operational state of the object, and obtaining input pattern arrays. Each input pattern array has a plurality of input vectors, while each input vector represents a time point and has input values representing a plurality of parameters indicating the current condition of the object. At least one processor generates estimate values based on a calculation that uses an input pattern array and the reference data to determine a similarity measure between the input values and reference data. The estimate values, in the form of an estimate matrix, include at least one estimate vector of inferred estimate values, and represents at least one time point that is not represented by the input vectors. The inferred estimate values are used to determine a future condition of the object.
Public/Granted literature
- US20130024416A1 Method of Sequential Kernel Regression Modeling For Forecasting and Prognostics Public/Granted day:2013-01-24
Information query
IPC分类:
G | 物理 |
G06 | 计算;推算或计数 |
G06N | 基于特定计算模型的计算机系统 |
G06N7/00 | 基于特定数学模式的计算机系统 |