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Active Diagnosis for Probabilistic Systems
[chapter]
2014
Lecture Notes in Computer Science
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This system is then diagnosable if the fault can always be detected, and the active diagnosis problem consists in controlling the system in order to ensure its diagnosability. ...
In this setting, the active diagnosis problem consists in deciding whether there exists some observationbased strategy that makes the system diagnosable with probability one. ...
Conclusion We studied the active diagnosis and safe active diagnosis problems for probabilistic discrete event systems, within a unifying POMDP framework. ...
doi:10.1007/978-3-642-54830-7_2
fatcat:fhcixh3iejclbpfyjgnoqeatpq
Special section on ``Applications of probabilistic graphical models in dependability, diagnosis and prognosis''
2017
Reliability Engineering & System Safety
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The consequence is a cumbersome activity for the analyst, often enforcing bias and partiality. ...
Reliability Engineering and System Safety Editorial
Special section on: Applications of Probabilistic Graphical Models in Dependability, Diagnosis and Prognosis In order to manage and to maintain in ...
doi:10.1016/j.ress.2017.04.017
fatcat:xz3c4s62fzattc3trrlgkpio5e
Normative Engineering Risk Management Systems
[chapter]
1993
Uncertainty in Artificial Intelligence
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For this application, the normative system is embedded in a real-time expert system. ...
This paper describes a normative system design that incorporates diagnosis, dynamic evolution, decision making; and information gathering. ...
William Gale for their contribution to the ideas developed in this paper. Grants from the National Science Foundation (SEF-9110462) and Bureau Veritas, Paris supported this work. ...
doi:10.1016/b978-1-4832-1451-1.50013-5
fatcat:vn5rlbjmajfppgjgbpboaflidi
Major Approaches to Medical Diagnosis and their Drawbacks
2009
Analele Universităţii "Dunărea de Jos" Galaţi: Fascicula III, Electrotehnică, Electronică, Automatică, Informatică
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Medical diagnosis is a dynamic and very complex field which needs special attention Our quest is for a system for medical diagnosis, that could model its search space efficiently and dynamically, while ...
Drawbacks of CAS ET • A major drawback of the system is inherited from bayesian nets: probabilistic inference is NP-difficult for multiply connected nets (i.e. with two or more paths between two nodes) ...
The matching mechanism is controlled by some special activation rules that select possible disorders into an active list. ...
doaj:905134691bea4c138e6de57ecc626f8b
fatcat:tve3gtzmineo3cpy6lpem2vysy
A Study of Probabilistic Diagnosis Method for Three Kinds of Internal Combustion Engine Faults Based on the Graphical Model
2019
Mathematical Problems in Engineering
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A strategy for increasing the accuracy rate of internal combustion engine (ICE) fault diagnosis based on the probabilistic graphical model is proposed. ...
method, a three-layer network with inference of probability is constructed, and both the material conditions and the signals collected from different engine parts are considered as the inputs of the system ...
It can be used for the diagnosis, and the diagnosis based on the probabilistic graphical model was achieved with high accuracy.
The Cylinder Score Fault. ...
doi:10.1155/2019/8156450
fatcat:yn6tn62tuvbszng7er6kswx2qq
Knowledge Processing
1995
IMIA Yearbook of Medical Informatics
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the use of KBS techniques in a rather unusual setting for an expert system for diagnosis and treatment of chronic hepatitis based on Chinese-medicine diagnostic and therapeutic techniques. ...
units, the ability to compete increasingly with the node's own activation level. ...
doi:10.1055/s-0038-1638035
fatcat:y3v37x75ybhdfdwg4qudqhioca
Improving ESB Capabilities through Diagnosis Based on Bayesian Networks and Machine Learning
2014
Journal of Software
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We propose a probabilistic approach to implement an analysis process. ...
We aim to improve the functionalities of an Enterprise Service Bus platform integrating monitoring and fault diagnosis capabilities. ...
Rish et al. in [6] present an active probing algorithm for probabilistic diagnosis based on the probes selection. ...
doi:10.4304/jsw.9.8.2206-2211
fatcat:rpdos64tp5crrny4ckufmmlgpy
A Survey on Proactive, Active and Passive Fault Diagnosis Protocols for WSNs: Network Operation Perspective
2018
Sensors
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] Nucleus management system [88] Sympathy-based approach [92] Mint-routing technique [91] Real-time monitoring [93] Analytical model [2] Lyapunov function [4] Probabilistic radio link [46] Blind forwarding ...
Although wireless sensor networks (WSNs) have been the object of research focus for the past two decades, fault diagnosis in these networks has received little attention. ...
Passive diagnosis Does not collect special data for fault diagnosis in the network [87] . Online fault diagnosis Finds faults during system runtime. ...
doi:10.3390/s18061787
pmid:29865210
pmcid:PMC6021939
fatcat:342xuyhfbrhfzfejptp6odhcqa
Probabilistic Health and Mission Readiness Assessment at System-Level
2019
Proceedings of the Annual Conference of the Prognostics and Health Management Society, PHM
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We illustrate and verify our methodology on a cooling system with an active feedback control loop, but our approach for mission readiness assessment is domain-independent, universally applicable, and typically ...
We propose a multi-step methodology to achieve such assessments using both Bayesian reasoning for diagnosis and prognosis and physics-based simulation models. ...
Based on its mission readiness diagnosis for which we detailed the generation process of Bayes nets for probabilistic reasoning, we see if the system requires maintenance prior to the mission or if the ...
doi:10.36001/phmconf.2019.v11i1.777
fatcat:i7hksso5jjeblgmoni4kke32oa
Adaptive Diagnosis in Distributed Systems
2005
IEEE Transactions on Neural Networks
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Index Terms-Diagnosis, probabilistic inference, Bayesian networks, information gain, computer networks, distributed systems, end-to-end transactions. ...
Active probing uses probabilistic reasoning techniques combined with information-theoretic approach, and allows a fast online inference about the current system state via active selection of only a small ...
We also thank EPP team, especially Herb Lee, Andy Frenkiel, and Marius Sabbath, for their collaboration on RAIL/EPP framework, and Douglas Griswold, Luis Moss, and Justin Ellis for providing the data and ...
doi:10.1109/tnn.2005.853423
pmid:16252819
fatcat:dtsmkddfejcbrgxauq3sejvumq
Principles of Diagnosis: Current Trends and a Report on the First International Workshop
1991
The AI Magazine
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Current research in this area addresses many problems, including managing and structuring probabilistic information, modeling physical systems, reasoning with defeasible assumptions, and interleaving deliberation ...
s Automated diagnosis is an important AI problem not only for its potential practical applications but also because it exposes issues common to all automated reasoning efforts and presents real challenges ...
Price Waterhouse, AAAI, ACM SIGART, Tom Gruber, and Bob Engelmore provided administrative support for Dx-90. ...
doi:10.1609/aimag.v12i4.921
dblp:journals/aim/Hamscher91
fatcat:36qrkyoqq5h4tinkn2b7g3vgba
Towards Active Diagnosis of Hybrid Systems leveraging Multimodel Identification and a Markov Decision Process
2015
IFAC-PapersOnLine
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This paper addresses active diagnosis of hybrid systems. ...
This paper addresses active diagnosis of hybrid systems. ...
This paper addresses active diagnosis of hybrid systems. ...
doi:10.1016/j.ifacol.2015.09.522
fatcat:t3rszn3ts5fk5m5tp6v7b363ye
Probabilistic graphic models applied to identification of diseases
2015
Einstein (São Paulo)
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In this text, we present basic use of probabilistic graphic models as tools to analyze causality in health conditions. ...
Decision-making is fundamental when making diagnosis or choosing treatment. ...
Real data must be submitted to different probabilistic systems and outcomes compared. ...
doi:10.1590/s1679-45082015rb3121
pmid:26154555
pmcid:PMC4943832
fatcat:wcuolty36nd6njrfo5buusbifm
Adaptive Probabilistic Neuro-Fuzzy System and its Hybrid Learning in Medical Diagnostics Task
2021
The Open Bioinformatics Journal
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In order to overcome arising restrictions and problems, a hybrid neuro-fuzzy system based on a probabilistic neural network and adaptive neuro-fuzzy interference system that allows solving the task in ...
Results: The proposed system solves the problem of classification in conditions of overlapping classes with the calculation of the membership levels of the formed diagnosis to various possible classes. ...
In a study [26] , the adaptive probabilistic neuro-fuzzy system for medical diagnosis was introduced. ...
doi:10.2174/18750362021140100123
fatcat:mzp2rqa3nnexxjkcwknesaml3m
Categorical and probabilistic reasoning in medical diagnosis
1978
Artificial Intelligence
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Within that context they compare MYCIN, PIP, CASNET, and INTERNIST-the four systems described in Chapters 5 through 8. ...
It was written for a special issue of Artificial Intelligence that dealt solely with applications of AI in biomedicine (Sridharan, 1978). ...
That selection depends on the probabilistic evaluation of each active hypothesis. ...
doi:10.1016/0004-3702(78)90014-0
fatcat:xr575rcvlzao5iigkcycwb6rha
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