Research On Speed Optimization Method Of Ocean Shipping Based On Intelligent Identification Of Sea State

The research on the optimization method of ocean-going ship speed is of great significance to realize energy-saving and emission-reduction of ships and intelligent navigation of ships.For ocean-going ships sailing on a fixed route,optimizing the speed is an effective way to save fuel and increase the efficiency of shipping companies.In order to realize that the ocean-going ship can intelligently adopt the best economic speed according to different sea conditions during the fixed-speed navigation process,and finally achieve the purpose of saving fuel,this paper conducts a research based on the target ship "Yuzhonghai",based on the fuel consumption of the target ship's historical operation And sea state data,a method for optimizing the speed of ocean-going ships based on intelligent identification of sea state was studied.Through verification,this method can provide decision support for the selection of the speed of ocean-going ships during constant-speed navigation.First,the historical operating data of the target ship's 13 voyages are extracted,and the knowledge base of the target ship's sea state category is established by improving the K-means clustering algorithm.Secondly,the intelligent segmentation method of ocean shipping routes was studied,and the target ship was selected from August 29,2018 to October 17,2018 from the port of San Luis in Brazil to Majishan Port in China as the target optimized voyage.In order to divide the route into a single course of the course,an intelligent recognition algorithm for the physical turning point was designed;in order to realize the intelligent recognition of the Shanghai condition category of each course of a single course,a sea state intelligent recognition method using an improved K nearest neighbor classification recognition algorithm was designed,and The accuracy of the improved K-nearest neighbor classification and recognition algorithm is 7.81%higher than that before the improvement,and the accuracy is 97.25%.Finally,this paper establishes fuel consumption models of fuel consumption and speed of each flight segment.Through the verification of real ship data,the overall error of the fuel consumption model established is 1.96%.Through the established fuel consumption model,the target optimization function and constraints of fuel consumption and speed of the total flight segment are calculated,and the speed of ocean-going ships is optimized through genetic optimization algorithm.The example analysis shows that the fuel consumption after optimization is 53.24t less than the fuel consumption calculated by the model before optimization,accounting for 2.42%,and the optimization effect is better.