Parallel Model-Based Diagnosis

2018 ◽  
pp. 547-580
Author(s):  
Kostyantyn Shchekotykhin ◽  
Dietmar Jannach ◽  
Thomas Schmitz
Keyword(s):  
Parallel Model ◽  
Model Based

A Global Parallel Model Based Design of Experiments Method to Minimize Model Output Uncertainty

2011 ◽  
Vol 74 (3) ◽  
pp. 688-716 ◽  
Author(s):  
Jason N. Bazil ◽  
Gregory T. Buzzard ◽  
Ann E. Rundell
Keyword(s):  
Design Of Experiments ◽  
Model Output ◽  
Parallel Model ◽  
Model Based ◽  
Output Uncertainty

MOI-MBO: Multiobjective Infill for Parallel Model-Based Optimization

2014 ◽  
pp. 173-186 ◽  
Author(s):  
Bernd Bischl ◽  
Simon Wessing ◽  
Nadja Bauer ◽  
Klaus Friedrichs ◽  
Claus Weihs
Keyword(s):  
Parallel Model ◽  
Model Based

scholarly journals Parallel model based fault detection algorithm for electronic parking brake system

2014 ◽  
Vol 15 (3) ◽  
pp. 483-494 ◽  
Author(s):  
B. J. Moon ◽  
H. G. Jung ◽  
S. G. Lee ◽  
D. H. Kim
Keyword(s):  
Fault Detection ◽  
Detection Algorithm ◽  
Brake System ◽  
Parallel Model ◽  
Model Based ◽  
Parking Brake

Texture segmentation parallel model based on the symmetric and asymmetric Gabor filters

1994 ◽  
Author(s):  
Yan Zhou ◽  
Harold G. Longbotham ◽  
Hong Deng
Keyword(s):  
Gabor Filters ◽  
Texture Segmentation ◽  
Parallel Model ◽  
Model Based

scholarly journals Parallel Model-Based Diagnosis on Multi-Core Computers

2016 ◽  
Vol 55 ◽  
pp. 835-887 ◽  
Author(s):  
Dietmar Jannach ◽  
Thomas Schmitz ◽  
Kostyantyn Shchekotykhin
Keyword(s):  
Search Strategy ◽  
Parallel Model ◽  
System Behavior ◽  
Actual System ◽  
Constraint Solver ◽  
Hitting Set ◽  
Detection Techniques ◽  
Model Based ◽  
Abstract Description ◽  
Domain Independent

Model-Based Diagnosis (MBD) is a principled and domain-independent way of analyzing why a system under examination is not behaving as expected. Given an abstract description (model) of the system's components and their behavior when functioning normally, MBD techniques rely on observations about the actual system behavior to reason about possible causes when there are discrepancies between the expected and observed behavior. Due to its generality, MBD has been successfully applied in a variety of application domains over the last decades. In many application domains of MBD, testing different hypotheses about the reasons for a failure can be computationally costly, e.g., because complex simulations of the system behavior have to be performed. In this work, we therefore propose different schemes of parallelizing the diagnostic reasoning process in order to better exploit the capabilities of modern multi-core computers. We propose and systematically evaluate parallelization schemes for Reiter's hitting set algorithm for finding all or a few leading minimal diagnoses using two different conflict detection techniques. Furthermore, we perform initial experiments for a basic depth-first search strategy to assess the potential of parallelization when searching for one single diagnosis. Finally, we test the effects of parallelizing "direct encodings" of the diagnosis problem in a constraint solver.

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