This thesis describes a research effort directed at producing a computational model based on artificially intelligent cellular automata. This model was developed for the purpose of learning a mapping from an input space to an output space. A specific problem that occurs in the mining industry was used to develop and test the model's ability to learn the mapping between a three-dimensional input volume and a three-dimensional output volume. In this case, the mapping was a consequence of the industrial processes used in mining as well as the properties of the material being mined. / Three main computational tools were combined in this work to form the complete mine stope prediction model. The three modules are a learning module, an optimisation module, and an overall network architecture. The overall network architecture is a 3-D lattice of cellular automata (CA) and has the capability to implicitly capture the complexities in shape that render other types of models arduous or inapplicable. The learning module uses a Discrete Time Cellular Neural Network (DTCNN) to store and recall information about a given mapping. The optimisation module uses the Simulated Annealing (SA) algorithm to perform a non-linear optimisation on the set of weights used by the DTCNN. / Variations of the model, and different experiments, were performed to test and explore the model in depth. Concepts such as "Small-Worlds" and "Forgetting Factor" were investigated. The applicability of a Partial Least Squares (PLS) model as an alternative to the DTCNN transition rule was also explored.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:QMM.33387 |
| Date | January 2000 |
| Creators | Côté, Brendan. |
| Contributors | Therien, Denis (advisor) |
| Publisher | McGill University |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Format | application/pdf |
| Coverage | Master of Science (School of Computer Science.) |
| Rights | All items in eScholarship@McGill are protected by copyright with all rights reserved unless otherwise indicated. |
| Relation | alephsysno: 001783022, proquestno: MQ70697, Theses scanned by UMI/ProQuest. |
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