Model-Based Diagnosis with Probabilistic Models

Gregory Provan

doi:10.1007/978-3-030-17728-7_12

Model-Based Diagnosis with Probabilistic Models

Gregory Provan

Research output: Chapter in Book/Report/Conference proceedings › Chapter › peer-review

Abstract

The literature on stochastic methods for diagnosis is extensive, covering domains such as medicine [59], process control [10], and electronics [12]. The use of uncertainty in modeling and inference arises due to several factors, including model uncertainty, measurement noise, external disturbance, and stochastic outcomes.

Original language	English
Title of host publication	Fault Diagnosis of Dynamic Systems
Subtitle of host publication	Quantitative and Qualitative Approaches
Publisher	Springer International Publishing
Pages	295-318
Number of pages	24
ISBN (Electronic)	9783030177287
ISBN (Print)	9783030177270
DOIs	https://doi.org/10.1007/978-3-030-17728-7_12
Publication status	Published - 1 Jan 2019

Access to Document

10.1007/978-3-030-17728-7_12

Cite this

@inbook{ec167419faa745d38f44f91fc373533c,

title = "Model-Based Diagnosis with Probabilistic Models",

abstract = "The literature on stochastic methods for diagnosis is extensive, covering domains such as medicine [59], process control [10], and electronics [12]. The use of uncertainty in modeling and inference arises due to several factors, including model uncertainty, measurement noise, external disturbance, and stochastic outcomes.",

author = "Gregory Provan",

note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2019.",

year = "2019",

month = jan,

day = "1",

doi = "10.1007/978-3-030-17728-7\_12",

language = "English",

isbn = "9783030177270",

pages = "295--318",

booktitle = "Fault Diagnosis of Dynamic Systems",

publisher = "Springer International Publishing",

address = "Switzerland",

}

TY - CHAP

T1 - Model-Based Diagnosis with Probabilistic Models

AU - Provan, Gregory

N1 - Publisher Copyright: © Springer Nature Switzerland AG 2019.

PY - 2019/1/1

Y1 - 2019/1/1

N2 - The literature on stochastic methods for diagnosis is extensive, covering domains such as medicine [59], process control [10], and electronics [12]. The use of uncertainty in modeling and inference arises due to several factors, including model uncertainty, measurement noise, external disturbance, and stochastic outcomes.

AB - The literature on stochastic methods for diagnosis is extensive, covering domains such as medicine [59], process control [10], and electronics [12]. The use of uncertainty in modeling and inference arises due to several factors, including model uncertainty, measurement noise, external disturbance, and stochastic outcomes.

UR - https://www.scopus.com/pages/publications/85147537216

U2 - 10.1007/978-3-030-17728-7_12

DO - 10.1007/978-3-030-17728-7_12

M3 - Chapter

AN - SCOPUS:85147537216

SN - 9783030177270

SP - 295

EP - 318

BT - Fault Diagnosis of Dynamic Systems

PB - Springer International Publishing

ER -

Model-Based Diagnosis with Probabilistic Models

Abstract

Access to Document

Other files and links

Fingerprint

Cite this