Self-Learning Algorithms for an Embedded Device Using Location Data on a Rolling Stock

Proceedings of 7th International Conference "Intelligent Technologies in Logistics and Mechatronics Systems (ITELMS’12)" 2012
Andrejs Mors-Jaroslavcevs, Anatolijs Ļevčenkovs

Objective of this paper is to design an embedded device for an intelligent rolling stock safety system which could provide a possibility for railway transport to avoid dangerous situations. The authors examine the algorithms used in artificial immune systems and ways how they can be used together and provide data for each one other via communication protocols. The authors review data analysis methods used to detect, predict and control undesirable rolling stock travel conditions.

Keywords
immune algorithms, classification, railway transport

Mors-Jaroslavcevs, A., Ļevčenkovs, A. Self-Learning Algorithms for an Embedded Device Using Location Data on a Rolling Stock. In: Proceedings of 7th International Conference "Intelligent Technologies in Logistics and Mechatronics Systems (ITELMS’12)", Lithuania, Panevėžys, 3-4 May, 2012. Kaunas: KTU, 2012, pp.1-1.

Publication language
English (en)