Computational Intelligence Techniques for Modelling the Critical Flashover Voltage of Insulators: From Accuracy to Comprehensibility
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InCollection{karampotsis_computational_2017,
-
title = "Computational {Intelligence} {Techniques} for
{Modelling} the {Critical} {Flashover} {Voltage} of
{Insulators}: {From} {Accuracy} to
{Comprehensibility}",
-
isbn13 = "978-3-319-60042-0",
-
URL = "https://doi.org/10.1007/978-3-319-60042-0_35",
-
abstract = "This paper copes with the problem of flashover voltage
on polluted insulators, being one of the most important
components of electric power systems. A number of
appropriately selected computational intelligence
techniques are developed and applied for the modelling
of the problem. Some of the applied techniques work as
black-box models, but they are capable of achieving
highly accurate results (artificial neural networks and
gravitational search algorithms). Other techniques, on
the contrary, obtain results somewhat less accurate,
but highly comprehensible (genetic programming and
inductive decision trees). However, all the applied
techniques outperform standard data analysis
approaches, such as regression models. The variables
used in the analyses are the insulator's maximum
diameter, height, creepage distance, insulator's
manufacturing constant, and also the insulator's
pollution. In this research work the critical flashover
voltage on a polluted insulator is expressed as a
function of the aforementioned variables. The used
database consists of 168 different cases of polluted
insulators, created through both actual and simulated
values. Results are encouraging, with room for further
study, aiming towards the development of models for the
proper inspection and maintenance of insulators.",
-
booktitle = "Advances in {Artificial} {Intelligence}: {From}
{Theory} to {Practice}: 30th {International}
{Conference} on {Industrial} {Engineering} and {Other}
{Applications} of {Applied} {Intelligent} {Systems},
{IEA}/{AIE} 2017, {Proceedings}, {Part} {I}",
-
publisher = "Springer",
-
author = "Evangelos Karampotsis and Konstantinos Boulas and
Alexandros Tzanetos and Vasilios P. Androvitsaneas and
Ioannis F. Gonos and Georgios Dounias and
Ioannis A. Stathopulos",
-
editor = "Salem Benferhat and Karim Tabia and Moonis Ali",
-
year = "2017",
-
address = "Arras, France",
-
month = jun # " 27-30",
-
DOI = "doi:10.1007/978-3-319-60042-0_35",
-
keywords = "genetic algorithms, genetic programming, artificial
neural networks, computational intelligence, critical
flashover voltage, Gravitational Search Algorithm,
inductive decision trees, insulators",
-
pages = "295--301",
- }
Genetic Programming entries for
Evangelos Karampotsis
Konstantinos Boulas
Alexandros Tzanetos
Vasilios P Androvitsaneas
Ioannis F Gonos
Georgios Dounias
Ioannis A Stathopulos
Citations