Improved Filtering for the QSIM Algorithm

Authors:
A. C. C. Say;S. Kuru
Affiliations:
-;-
Venue:
IEEE Transactions on Pattern Analysis and Machine Intelligence
Year:
1993

Citing 4
Cited 6

Qualitative simulation

Artificial Intelligence
Qualitative reasoning: modeling and simulation with incomplete knowledge

Automatica (Journal of IFAC)
Qualitative system identification: deriving structure from behavior

Artificial Intelligence
Higher-Order Derivative Constraints in Qualitative Simulation

Higher-Order Derivative Constraints in Qualitative Simulation

L'Hôpital's Filter for QSIM

IEEE Transactions on Pattern Analysis and Machine Intelligence
Making Use of Contradictory Behavior Information in Qualitative Reasoning

IEEE Transactions on Pattern Analysis and Machine Intelligence
Sound and complete qualitative simulation is impossible

Artificial Intelligence
Qualitative simulation and related approaches for the analysis of dynamic systems

The Knowledge Engineering Review
Causes of ineradicable spurious predictions in qualitative simulation

Journal of Artificial Intelligence Research
Random generation of monotonic functions for Monte Carlo solution of qualitative differential equations

Automatica (Journal of IFAC)

Quantified Score

Hi-index	0.15

Visualization

Abstract

A source of spurious predictions inside the qualitative simulation algorithm QSIM proposed by B. Kuiper (1986) is identified. The proposed solution involves the use of interval corresponding values for filtering inconsistent states and does not require any additions or restrictions in the input set, unlike the other approaches to the spurious prediction elimination problem. The time and space complexities of the algorithm are not affected by the modification.