Analýza predikčních modelů určených pro financování základní dopravní obslužnosti území

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F06%3A00003602" target="_blank" >RIV/00216275:25410/06:00003602 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216275:25410/06:00005643

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Prediction Models Analysis of Financing of Basic Transport Services

Popis výsledku v původním jazyce

The paper deals with a prediction models analysis. These models are determined for a financing of basic transport services (BTS). Importance of the prediction model (PM) lies in possibility of the Regional Authority employees to flexibly respond to requirements of a bus carrier that provides BTS within a specified region. The requirements are connected with an obligation of the public services contract conclusion. For the PM creation it was used neural networks. The achieved results of PM that is basedon the neural networks were compared with results of prediction of other models. Prediction algorithms in these models are regression trees and multiple regression. A future volume of the financial resources determination for bus line connections financing should lead to a more effective usage of budget resources. Public administration effectiveness increase and related public administration quality increase count among trends in the field of good governance under sustainable development

Název v anglickém jazyce

Prediction Models Analysis of Financing of Basic Transport Services

Popis výsledku anglicky

The paper deals with a prediction models analysis. These models are determined for a financing of basic transport services (BTS). Importance of the prediction model (PM) lies in possibility of the Regional Authority employees to flexibly respond to requirements of a bus carrier that provides BTS within a specified region. The requirements are connected with an obligation of the public services contract conclusion. For the PM creation it was used neural networks. The achieved results of PM that is basedon the neural networks were compared with results of prediction of other models. Prediction algorithms in these models are regression trees and multiple regression. A future volume of the financial resources determination for bus line connections financing should lead to a more effective usage of budget resources. Public administration effectiveness increase and related public administration quality increase count among trends in the field of good governance under sustainable development

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2006

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

WSEAS Transactions on Systems

ISSN

1109-2777

e-ISSN

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Svazek periodika

1

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

GR - Řecká republika

Počet stran výsledku

8

Strana od-do

211-218

Kód UT WoS článku

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EID výsledku v databázi Scopus

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