Combining Event Processing and Support Vector Machines for Automated Flight Diversion Predictions
نویسندگان
چکیده
Multi-modal logistics chains are those transportation processes in which different modes of transportation are involved for the delivery of goods. These modes are adopted in consecutive legs, which have to be synchronized. An example scenario is the delivery of goods from a production center in New York, USA, to a plant in Utrecht, the Netherlands. The transportation chain consists of two legs: (i) an aicraft carries the goods from John F. Kennedy International Airport (New York) to Schiphol (Amsterdam) and (ii) a truck sent by a Logistics Service Provider (LSP) transports the cargo from Dutch airport to Utrecht. The growth in international and inter-continental trade has led to a significant increase of multi-modal transports worldwide. Therefore, guaranteeing its efficiency is of crucial relevance for the successful completion of such transportation processes. In the example scenario, the goal of the LSP is to deliver the goods in time, in conformance with the Service Level Objectives (SLOs).
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