Polynomial Temporal Band Sequences for Analog Diagnosis
Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence. Diagnosis and Qualitative Reasoning. Pages 474-478.
Abstract
In [Loiez and Taillibert 96a] we proposed a new way to model components and physical quantities in the framework of Model-based Diagnosis applied to analog systems. Components were represented by equations of the form " f+g'=O " where f and g are functions of observable quantities of the system to be diagnosed ; observations were represented by temporal band sequences (sets of consecutive trapezoids encompassing the observations); consistency checking was done by integration. The present paper generalizes the observation representation to temporal bands defined by any polynomial function. It shows that this extension not only allows a better approximation of observations but also that models of components can now be represented by equations relating derivatives of any order (f+g'+h"+ ... =O) and involving any polynomial functions, which improves dramatically the ease of modeling analog systems.
@inproceedings{ijcai1997p70,
title = {Polynomial Temporal Band Sequences for Analog Diagnosis},
author = {Loiez, Étienne and Taillibert, Patrick},
booktitle = {Proceedings of the Fifteenth International Joint Conference on
Artificial Intelligence, {IJCAI-97}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Martha E. Pollack},
pages = {474--478},
year = {1997},
note = {Diagnosis and Qualitative Reasoning},
url = {https://ijcai.org/proceedings/1997/70},
}
TY - CPAPER TI - Polynomial Temporal Band Sequences for Analog Diagnosis AU - Loiez, Étienne AU - Taillibert, Patrick T2 - Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, IJCAI-97 PB - International Joint Conferences on Artificial Intelligence PY - 1997 SP - 474 EP - 478 UR - https://ijcai.org/proceedings/1997/70 ER -Copied
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