Publikace detail

A genetic algorithm-based data mining approach to modeling of public transport demand

Autoři: Bartoníček Tomáš

Rok: 2004

Druh publikace: článek ve sborníku

Název zdroje: Európske financie - Teória, politika a prax

Název nakladatele: Univerzita Mateja Bela v Banskej Bystrici

Místo vydání: Banská Bystrica

Strana od-do: 6

Tituly:

Jazyk	Název	Abstrakt	Klíčová slova
cze	Využití genetických algoritmů na bázi data miningu v modelování poptávky po veřejné dopravě	In this paper is presented a proposal of genetic algorithm for knowledge discovery process. Data mining (the process of extracting trends or patterns from data) is used in database of bus lines carriers here. The aim is to find link between bus line revenue and significant factors affecting public transport demand. There are many data mining methods used in knowledge discovery in databases. Genetic algorithms belong to the field of evolutionary computation and in special case could be used in data mining. There is shown how to change the basic form of genetic algorithm (representation, operators etc.) to obtain important knowledge about transport demand in the paper.
eng	A genetic algorithm-based data mining approach to modeling of public transport demand	In this paper is presented a proposal of genetic algorithm for knowledge discovery process. Data mining (the process of extracting trends or patterns from data) is used in database of bus lines carriers here. The aim is to find link between bus line revenue and significant factors affecting public transport demand. There are many data mining methods used in knowledge discovery in databases. Genetic algorithms belong to the field of evolutionary computation and in special case could be used in data mining. There is shown how to change the basic form of genetic algorithm (representation, operators etc.) to obtain important knowledge about transport demand in the paper.	genetic algorithms, public transport demand, data-mining

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