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The matlab program for ship power load prediction has shown to have a good predictive performance, due to the reliable data used in its application. One possible way to further improve this program is to expand its capabilities to include more diverse data sets. Additionally, incorporating machine learning algorithms into the program could enhance its accuracy and efficiency, allowing for more precise predictions and better decision-making in the management of ship power loads. Furthermore, exploring the potential for integrating this program with other ship management systems could provide a more comprehensive solution for optimizing ship operations and improving overall performance.