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Metrics for Offline Evaluation of Prognostic PerformancePrognostic performance evaluation has gained significant attention in the past few years. Currently, prognostics concepts lack standard definitions and suffer from ambiguous and inconsistent interpretations. This lack of standards is in part due to the varied end-user requirements for different applications, time scales, available information, domain dynamics, etc. to name a few. The research community has used a variety of metrics largely based on convenience and their respective requirements. Very little attention has been focused on establishing a standardized approach to compare different efforts. This paper presents several new evaluation metrics tailored for prognostics that were recently introduced and were shown to effectively evaluate various algorithms as compared to other conventional metrics. Specifically, this paper presents a detailed discussion on how these metrics should be interpreted and used. These metrics have the capability of incorporating probabilistic uncertainty estimates from prognostic algorithms. In addition to quantitative assessment they also offer a comprehensive visual perspective that can be used in designing the prognostic system. Several methods are suggested to customize these metrics for different applications. Guidelines are provided to help choose one method over another based on distribution characteristics. Various issues faced by prognostics and its performance evaluation are discussed followed by a formal notational framework to help standardize subsequent developments.
Document ID
Document Type
Preprint (Draft being sent to journal)
Saxena, Abhinav
(SGT, Inc. Moffett Field, CA, United States)
Celaya, Jose
(SGT, Inc. Moffett Field, CA, United States)
Saha, Bhaskar
(Mission Critical Technologies, Inc. Moffett Field, CA, United States)
Saha, Sankalita
(Mission Critical Technologies, Inc. Moffett Field, CA, United States)
Goebel, Kai
(NASA Ames Research Center Moffett Field, CA, United States)
Date Acquired
August 25, 2013
Publication Date
January 30, 2010
Publication Information
ISSN: 2153-2648
Subject Category
Engineering (General)
Report/Patent Number
Funding Number(s)
WBS: WBS 645846.
Distribution Limits
Public Use Permitted.
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