A program searching for a functional dependence using genetic programming with coefficient adjustment
Created by W.Langdon from
gp-bibliography.bib Revision:1.8154
- @InProceedings{Hlavac:2016:SCSP,
-
author = "Vladimir Hlavac",
-
title = "A program searching for a functional dependence using
genetic programming with coefficient adjustment",
-
booktitle = "2016 Smart Cities Symposium Prague (SCSP)",
-
year = "2016",
-
month = "26-27 " # may,
-
keywords = "genetic algorithms, genetic programming",
-
DOI = "doi:10.1109/SCSP.2016.7501014",
-
abstract = "When modelling many traffic problems, it is necessary
to find the functional dependence of the output of two
input variables. This task can be solved by a neural
network, by using some spline interpolation or
polynomials, etc. These approaches can produce a model,
but its internal description is unreadable and its
transfer to another program can be difficult.
Therefore, a program to determine this functional
dependence using genetic programming has been
developed. The result is prepared in such a way that it
can be transferred into a source code of another
program, or copied to an MS Excel sheet. The program
reads data available as triplets, [[x, y], z], and
looks for their functional interdependencies by using a
selected set of elementary functions and a vector of
multiplicative constants. The input data do not have to
meet any additional conditions. They can be defined on
measured intervals, or even as individual points. For a
successful outcome, the only condition is to have a
sufficient amount of data. For some functions, the
level of noise has to be determined in order to make
the model complete. In this case, noise characteristics
can be evaluated from the results of the program.",
-
notes = "Also known as \cite{7501014}
Department of Applied Informatics in Transportation,
Czech Technical University in Prague, Prague, Czech
Republic",
- }
Genetic Programming entries for
Vladimir Hlavac
Citations