Name
Abstract | ||
|---|---|---|
This paper presents a realistic study of applying a gene regulatory model to financial prediction. The combined adaptation of evolutionary and developmental processes used in the model highlight its suitability to dynamic domains, and the results obtained show the potential of this approach for real-world trading. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/978-3-662-45523-4_21 | Lecture Notes in Computer Science |
Field | DocType | Volume |
Gene,Computer science,Technical indicator,Operations research,Artificial intelligence,Financial prediction,Gene regulatory network,Grammatical evolution,Network model,Machine learning | Conference | 8602 |
ISSN | Citations | PageRank |
0302-9743 | 1 | 0.35 |
References | Authors | |
5 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Miguel Nicolau | 1 | 125 | 13.86 |
| Michael O'Neill | 2 | 876 | 69.58 |
| Anthony Brabazon | 3 | 918 | 98.60 |