Modeling cargo theft probability in rail transport using arificial neural network
Authors:
- Augustyn Lorenc,
- Małgorzata Kuźnar
Abstract
The paper focuses on the safety of railway transport and the possibility of a risk appearance in a supply chain using rail vehicles as a mode of transport. The rail transport plays a significant role in the international market for goods forwarding and transportation. In this paper, authors present own model used to predict the probability of cargo theft. In the mining and metallurgical industry, adequate protection and securing the transported cargo is extremely important. In the Silesia - industrial region of Poland, every year there are over one thousand cases of theft. The cost of such incidents is higher than one million euro per year. The railway security guards use a low-cost method to make cargo harder to steal or use the newest technology like drone monitoring system to help find the theft cargo and catch the thieves. In this paper, authors present the method which uses factors, such as the type of cargo, type of wagons, distance, delays, train speed and others, to predict the possibilities of theft during each transport case. This method can be used to develop a support system to plan the area of drone monitoring and security control of the rail line infrastructure. The presented method uses Artificial Neural Networks (ANN) as the core of the support system. The developed model can be also used to support decisions about additional cargo insurance for high risk of theft cases. This method is based on the latest data of disruptions in the supply chain, which allow appropriate response to supply chain disruptions in order to minimize losses and costs associated with losses.
- Record ID
- CUTb9562f289a484757b5b6f05e8da3b029
- Publication categories
- ; ;
- Author
- Pages
- 306-311
- Other elements of collation
- rys.; tab.; wykr.; Bibliografia (na s.) - 311; Bibliografia (liczba pozycji) - 18; Oznaczenie streszczenia - Abstr.
- Book
- CLC2 2018 Logistics, Distribution, Transport & Management : 8th Carpathian Logistics Congress, December 3rd-5th 2018, Prague, Czech Republic, EU : conference proceedings, Carpathian Logistics Congress : CLC, 2018, Ostrava, TANGER Ltd., ISBN 978-80-87294-88-8
- Keywords in English
- rail transport securing, supply chain disruption, theft of the cargo, drone monitoring, security support system, artificial neural network
- URL
- https://www.confer.cz/clc/2018/2581-modeling-cargo-theft-probability-in-rail-transport-using-arifitial-neural-network Opening in a new tab
- Language
- eng (en) English
- License
- Score (nominal)
- 5
- Additional fields
- Indeksowana w: Web of Science
- Uniform Resource Identifier
- https://cris.pk.edu.pl/info/article/CUTb9562f289a484757b5b6f05e8da3b029/
- URN
urn:pkr-prod:CUTb9562f289a484757b5b6f05e8da3b029
* presented citation count is obtained through Internet information analysis, and it is close to the number calculated by the Publish or PerishOpening in a new tab system.