master's thesis
Neural network based traffic prediction

Matea Ravnjak (2015)
Sveučilište u Zagrebu
Fakultet prometnih znanosti
Inteligentni transportni sustavi i logistika
Zavod za inteligentne transportne sustave
Metadata
TitlePredviđanje količine prometa zasnovano na neuronskoj mreži
AuthorMatea Ravnjak
Mentor(s)Edouard Ivanjko (thesis advisor)
Abstract
U ovom radu kreirana je neuronska mreža s ciljem predviđanja količine prometa na transportnoj mreži. Pri tome se misli na cestovni transport (broj vozila) te na telekomunikacijski promet, odnosno prijenos podataka. Na osnovu ulaznih varijabli prikupljenih tijekom određenog vremena, predviđa se broj vozila odnosno količina podatkovnog prometa za idući vremenski interval. Korištena je višeslojna struktura neuronske mreže, a rezultati pokazuju da je neuronska mreža sposobna prilikom učenja aproksimirati funkciju ulaznih i izlaznih varijabli uz visoku točnost.
Keywordsartificial intelligence neural networks prediction transport systems multi-layer architecture road network telecommunication network
Parallel title (English)Neural network based traffic prediction
Committee MembersEdouard Ivanjko
Štefica Mrvelj
Sadko Mandžuka
Hrvoje Gold
GranterSveučilište u Zagrebu
Fakultet prometnih znanosti
Lower level organizational unitsInteligentni transportni sustavi i logistika
Zavod za inteligentne transportne sustave
PlaceZagreb
StateCroatia
Scientific field, discipline, subdisciplineTECHNICAL SCIENCES
Traffic and Transport Technology
Postal and Telecommunications Traffic
Study programme typeuniversity
Study levelgraduate
Study programmeRoad Transport, Railway Transport, Water Transport, Air Transport, Postal Transport, Information and Communications Traffic, Urban Transport
Academic title abbreviationmag. ing. traff.
Genremaster's thesis
Language Croatian
Defense date2015-09-24
Parallel abstract (English)
In this paper, neural network is created in order to predict the amount of traffic in the transport networks. This refers to road transport (number of vehicles) and telecommunication traffic, i.e. data transfer. Based on the input variables collected during a certain time, neutral network made predictions for number of vehicles and the amount of data traffic for the next time interval. Multilayer structure neutral network is used, and the results show that the neural network is capable to learn approximate function of input and output variables with high accuracy.
Parallel keywords (Croatian)umjetna inteligencija neuronske mreže predviđanje transportni sustavi višeslojna arhitektura cestovna mreža telekomunikacijska mreža
Resource typetext
Access conditionOpen access
Terms of usehttp://rightsstatements.org/vocab/InC/1.0/
URN:NBNhttps://urn.nsk.hr/urn:nbn:hr:119:749606
CommitterMojca Brenko-Puzak