A prediction method is proposed based on RBF neural network through in-depth study of power load of ships. Before predicting the ship's power load, it is necessary to pre-process various data of the ship, screen and clean the abnormal data, and then normalise the normal samples, and finally construct a model to process the data and optimise the model according to the results. Various data of an electric propulsion ship are selected as the input reference of the model, and a prediction model is established using Matlab. The design method is shown to be one of the methods with high prediction accuracy according to the experimental results, and shows high model credibility in prediction.
Load Forecasting for Electric Propulsion Vessels Based on RBF Neural Network
28.09.2024
966742 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Electric propulsion of vessels
Engineering Index Backfile | 1918
|Turbo-electric propulsion for vessels
Engineering Index Backfile | 1909
|Daily Electric Load Forecasting Using Artificial Neural Network
Online Contents | 1995
|Diesel Electric Propulsion for Offshore Vessels
British Library Conference Proceedings | 2008
|