Pregled bibliografske jedinice broj: 1153909
Using Neural Networks for Bicycle Route Planning
Using Neural Networks for Bicycle Route Planning // Applied Sciences-Basel, 11 (2021), 21; 10065, 21 doi:10.3390/app112110065 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 1153909 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Using Neural Networks for Bicycle Route Planning
Autori
Đerek, Jurica ; Sikora, Marjan ; Kraljević, Luka ; Russo, Mladen
Izvornik
Applied Sciences-Basel (2076-3417) 11
(2021), 21;
10065, 21
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
GIS ; multiple criteria analysis ; neural networks ; bicycle ; routes ; tourists ; travelling salesman problem ; recurrent NN ; digital elevation model
Sažetak
This paper presents the usage of artificial neural networks (NNs) in bicycle route planning. This research aimed to check the possibility of NNs to transfer human expertise in bicycle route design by training the NN on an already established set of bicycle routes and then using the trained NN to design the routes on the novel area. We created two NNs capable of choosing the best route among the given road network by training them on two different areas. The bicycle routes produced by NNs were the same at best and had 75% overlap at the worst compared to those produced by human experts. Furthermore, the mean square error for all of our NN models varied from 0.015 and 0.081. We compared this new approach to the traditional multicriteria GIS (geographic information system) analysis (MA) that requires the human expert to define the bicycle route selection criteria. The benefit of using NN over the MA was that the NN directly transfers the human expertise to a model. In contrast, the MA needs the expert to select multiple criteria and adjust their weights carefully.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
POVEZANOST RADA
Projekti:
EK-EFRR-KK.01.1.1.07.0079 - VITA – Virtualna Telemedicinska Asistencija (VITA) (Russo, Mladen, EK - Jačanje kapaciteta za istraživanje, razvoj i inovacije, referentni broj poziva KK.01.1.1.07) ( CroRIS)
Ustanove:
Fakultet elektrotehnike, strojarstva i brodogradnje, Split
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus