Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
A neural network approach to mitigation of vehicle schedule disturbances
In all transportation industries, when planned schedules are modified by delays, breakdowns or peaks of demand, ‘real‐time’ human decision making takes place. Dispatchers in charge of traffic control usually are allowed a very short time to make decisions that should mitigate the negative effects resulting from the disturbance. This paper aims to demonstrate the feasibility of a dispatch decision support system that could decrease the work load for the dispatcher and improve the quality of decisions. The proposed neural network, with the ability to adapt or learn from examples of decisions, can simulate the dispatcher's decision process.
A neural network approach to mitigation of vehicle schedule disturbances
In all transportation industries, when planned schedules are modified by delays, breakdowns or peaks of demand, ‘real‐time’ human decision making takes place. Dispatchers in charge of traffic control usually are allowed a very short time to make decisions that should mitigate the negative effects resulting from the disturbance. This paper aims to demonstrate the feasibility of a dispatch decision support system that could decrease the work load for the dispatcher and improve the quality of decisions. The proposed neural network, with the ability to adapt or learn from examples of decisions, can simulate the dispatcher's decision process.
A neural network approach to mitigation of vehicle schedule disturbances
Vukadinović, Katarina (Autor:in) / Teodorović, Dušan (Autor:in) / Pavković, Goran (Autor:in) / Rosić, Slobodan (Autor:in)
Transportation Planning and Technology ; 20 ; 93-102
01.09.1996
10 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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