Research on the Speed Optimization Model Based on BP Neural Network and Genetic Algorithm (GA)

摘要

In this paper, a larger number of data was adopted, which is collectedduring the operation the 20000t Jianghai direct bulk carrier ship sailingon the Zhoushan Maanshan route. The dataset is trained based on thepower model combined with the hull-propeller-engine matching modeland BP artificial neural network. As the training progresses, the shippower model parameters are continuously modified, and the fuelconsumption rate is added to obtain the ship real time fuel consumptionprediction model. Finally, based on the model, a speed-fuel consumptionoptimization model based on genetic algorithm is established, and theenergy saving speed is obtained.