Name
Abstract | ||
|---|---|---|
In this paper are presented classification methods with use of two-dimensional three-state cellular automata. This methods are probabilistic forms of cellular automata rule modified from wide known almost deterministic rule designed by Fawcett. Fawcetts rule is modified into two proposed forms partially and fully probabilistic. The effectiveness of classifications of these three methods is analysed and compared. The classification methods are used as the rules in the two-dimensional three-state cellular automaton with the von Neumann and Moore neighbourhood. Preliminary experiments show that probabilistic modification of Fawcett's method can give better results in the process of reconstruction (classification) than the original algorithm. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.15439/2016F409 | 2016 Federated Conference on Computer Science and Information Systems (FedCSIS) |
Keywords | Field | DocType |
probabilistic 2D cellular automata rules,binary classification,two-dimensional three-state cellular automata,deterministic rule,Fawcetts rule,partially probabilistic form,fully probabilistic form,von Neumann-Moore neighbourhood,reconstruction process | Cellular automaton,Quantum finite automata,Algorithm design,Binary classification,Computer science,Automaton,Algorithm,Artificial intelligence,Probabilistic logic,Probabilistic relevance model,Von Neumann architecture,Machine learning | Conference |
Volume | ISSN | ISBN |
8 | 2300-5963 | 978-1-5090-0046-3 |
Citations | PageRank | References |
1 | 0.42 | 3 |
Authors | ||
1 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Miroslaw Szaban | 1 | 34 | 8.81 |