Generalizing from case studies: a case study
ML92 Proceedings of the ninth international workshop on Machine learning
Bivariate splits and consistent split criteria in dichotomous classification trees
Bivariate splits and consistent split criteria in dichotomous classification trees
Solving the multiple instance problem with axis-parallel rectangles
Artificial Intelligence
Concept learning in the absence of counterexamples: an autoassociation-based approach to classification
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
One-Class Classification by Combining Density and Class Probability Estimation
ECML PKDD '08 Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I
Learning automaton based on-line discovery and tracking of spatio-temporal event patterns
PRICAI'10 Proceedings of the 11th Pacific Rim international conference on Trends in artificial intelligence
A new frontier in novelty detection: pattern recognition of stochastically episodic events
ACIIDS'11 Proceedings of the Third international conference on Intelligent information and database systems - Volume Part I
Canadian AI'12 Proceedings of the 25th Canadian conference on Advances in Artificial Intelligence
On the pattern recognition and classification of stochastically episodic events
Transactions on Compuational Collective Intelligence VI
| Hi-index | 0.00 |
Simulation, as an art and a science, deals with the issue of allowing the practitioner to model events using their respective probability distributions. Thus, it is customary for simulations to model the behaviour of accidents, telephone calls, network failures etc. In this paper, we consider a relatively new field, namely that of modelling episodic events such as earthquakes, nuclear explosions etc. The difficulty with such a modelling process is that most of the observations appear as noise. However, when the episodic event does occur, its magnitude and features far overshadow the background, as one observes after a seismic event. In this paper, we demonstrate how the effect of a particular form of episodic event can be modelled as it propagates through the underlying background noise. Furthermore, we illustrate how the subsequent decay of the event can also be modelled and simulated. In demonstrating this concept, we utilize the exemplar scenario posed by the Comprehensive Nuclear-Test-Ban Treaty (CTBT), and model the propagation and decay of radionuclides, emitted from clandestine, subterranean nuclear detonations, through the background levels resulting from the global nuclear industry.