Name
Abstract | ||
|---|---|---|
The mass assignment ID3 (MA-ID3) algorithm for generating linguistic decision trees is introduced together with the mass assignment semantics for linguistic variables. The potential of this algorithm for learning control rules is illustrated by means of the Van de Pol system. A data set of control paths is generated using an existing on-line controller. This is then used to generate a set of quantified linguistic control rules. The effectiveness and robustness of this rule-base is then demonstrated. |
Year | DOI | Venue |
|---|---|---|
2000 | 10.1016/S0218-4885(00)00004-6 | International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems |
Keywords | Field | DocType |
decision tree,mass assignment | Decision tree,Control theory,Computer science,Robustness (computer science),Artificial intelligence,ID3,Linguistics,Semantics,Machine learning | Journal |
Volume | Issue | ISSN |
8 | 1 | 0218-4885 |
Citations | PageRank | References |
1 | 0.36 | 3 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| James F. Baldwin | 1 | 25 | 4.57 |
| Jonathan Lawry | 2 | 172 | 19.06 |