Name
Abstract | ||
|---|---|---|
Abstract Gene Expression Programming (GEP) is a popular and established evolutionary algorithm for automatic generation of computer programs. In recent decades, GEP has undergone rapid advancements and developments. A number of enhanced GEPs have been proposed to date and the real world applications that use them are also multiplying fast. In view of the steadfast growth of GEP and its importance ... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/MCI.2017.2708618 | IEEE Computational Intelligence Magazine |
Keywords | Field | DocType |
Gene expression,Programming,Computational modeling,Encoding,Algorithm design and analysis | Gene expression programming,Algorithm design,Evolutionary algorithm,Review article,Computer science,Mechanism design,Artificial intelligence,Genetic algorithm,Machine learning,Encoding (memory) | Journal |
Volume | Issue | ISSN |
12 | 3 | 1556-603X |
Citations | PageRank | References |
8 | 0.56 | 74 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jing-hui Zhong | 1 | 380 | 33.00 |
| Liang Feng | 2 | 118 | 14.17 |
| Yew-Soon Ong | 3 | 4205 | 224.11 |