Design And Implementation Of Logistics Transport Early-warning Model

With the rapid development of logistics industry, logistics has gradually evolved into a complex processes. Transport processes occupy an important position in the logistics activities. In the transport process, how to prevent the transportation accidents, ensure the safe of transportation, reduce loss, has become the problem in the field of logistics transportation.Concerning the security issue in the current transport logistics, five influence aspects of transport logistics were discussed, including people, vehicles, roads, environment and carried goods. Then the early-warning model of transport logistics was constructed. With the model, the early-warning information of transport logistics could be obtained. Then we take corresponding measures to avoid transport accidents. The construction of early-warning model contains:①constructing unitary and binary early-warning model based on ontology and rules,②multi early-warning model of logistics transport based on fuzzy comprehensive evaluation. The former construct the early-warning ontology, analyzing the early-warning rules, establish the early-warning rule library by using the concept and property. This paper uses the rule-based inference engine which is supplied by Jena inference subsystem, then realize early warning of the logistics transport. Because the former can't complete the multi early-warning, the multi early-warning model based on fuzzy comprehensive evaluation is proposed. The early-warning indexes and the weight of each index were determined using the Analytic Hierarchy Process and the expert scoring method. Then based on the multi-level Fuzzy Comprehensive Evaluation method, the early-warning information of transport logistics could be obtained by calculating the early-warning level. It reduces the rate of transportation accident and the unnecessary loss.In sum, it can complete the early-warning function through the construction of early warning model. Then it provides the safe running for the vehicles to avoid the road transport accidents.