MODIFIED METHOD OF GRAVITY MODEL APPLICATION FOR TRANSATLANTIC AIR TRANSPORTATION
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21260%2F15%3A00229957" target="_blank" >RIV/68407700:21260/15:00229957 - isvavai.cz</a>
Result on the web
<a href="http://www.nnw.cz" target="_blank" >http://www.nnw.cz</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.14311/NNW.2015.25.011" target="_blank" >10.14311/NNW.2015.25.011</a>
Alternative languages
Result language
angličtina
Original language name
MODIFIED METHOD OF GRAVITY MODEL APPLICATION FOR TRANSATLANTIC AIR TRANSPORTATION
Original language description
Air transportation between Europe and the U.S. is becoming more and more significant. It can only hardly be replaced by other means of transportation, since its biggest advantages include speed and reliability. Air transportation forecasting is importantfor planning the development of airports and related infrastructure, and of course also for air carriers. Therefore, it is important to forecast the number of flights between selected airports in Europe and the U.S. and the number of transported persons. A gravity model is usually used for this forecasting. Determination of coefficients which significantly affect results of the formulas used in the gravity model is crucial. Coefficients are, as a rule, computed by an iterative algorithm implementing the gradient method. This technique has some limitations if the state space is inappropriate. Moreover, the exponent parameter in the formula is obviously fixed. We have chosen the new method of differential evolution to determine the gravi
Czech name
—
Czech description
—
Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
JU - Aeronautics, aerodynamics, aeroplanes
OECD FORD branch
—
Result continuities
Project
—
Continuities
R - Projekt Ramcoveho programu EK
Others
Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Neural Network World
ISSN
1210-0552
e-ISSN
—
Volume of the periodical
25
Issue of the periodical within the volume
2
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
15
Pages from-to
203-217
UT code for WoS article
000354664000007
EID of the result in the Scopus database
—