Name
Abstract | ||
|---|---|---|
The increasing complexity of problems in the context of system modeling is leading to a new epistemological approach able to provide a representation which allows from one hand, to model complex phenomena with the support of mathematical and computational instruments, and on the other hand able to capture the global system description. In this article is presented a methodology for complex dynamical systems modeling which is an extension of the supervised learning paradigm. The theoretical aspects of our methodology are introduced and then two different and heterogeneous case studies are presented. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.4018/jalr.2010102101 | IJALR |
Keywords | Field | DocType |
new epistemological approach,system modeling,complex phenomenon,heterogeneous case study,global system description,supervised learning paradigm,increasing complexity,computational instrument,theoretical aspect,complex systems modelling,complex dynamical systems modeling,complex systems,immunology,complex system,prediction | Complex system,Computer science,Global system,Supervised learning,Dynamical systems theory,Systems modeling,Artificial intelligence,Machine learning,Complex systems biology | Journal |
Volume | Issue | Citations |
1 | 1 | 0 |
PageRank | References | Authors |
0.34 | 5 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Walter Quattrociocchi | 1 | 582 | 42.16 |
| Daniela Latorre | 2 | 0 | 0.34 |
| Elena Lodi | 3 | 0 | 0.34 |
| Mirco Nanni | 4 | 1412 | 84.47 |