
handle: 11012/179195
The paper discusses the influence of function set structure onto efficiency of GPA (Genetic Programming Algorithms), and hierarchical algorithms like GPA-ES (GPA with Evolutionary Strategy to separate parameter optimization) algorithm efficiency. On the foreword, the discussed GPA algorithm is described. Then there is depicted function set and common requirements to its structure. On the end of this contribution, the test examples and environment as well as results of measurement of influence of superfluous functions presence in the used function set is discussed.
Function set structure, Electronic computers. Computer science, Genetic Programming Algorithm, Efficiency, QA75.5-76.95, mutually replaceable functions, Function set, Inapplicable functions
Function set structure, Electronic computers. Computer science, Genetic Programming Algorithm, Efficiency, QA75.5-76.95, mutually replaceable functions, Function set, Inapplicable functions
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
