Improved GA-BP Based Early Warning of Warehousing and Logistics Risk in Cruise Ship Construction

Risks associated with the process of loading/unloading and transfer, inspection, receiving and storage of materials for construction of cruise ships are studied in terms of machinery, materials, law and environment. A risk evaluation index system is devised. The network model is constructed for minimum error in early warning of the risk. The circle modification algorithm and experimental design method are introduced into the basic GA-BP neural network to improve its global searching ability and convergence speed. The design is verified through experiments.