An improved LSSVM-based method for prediction demand for maritime logistics support material

The primary task of carrier formation maritime logistics support is to supply ammunition, oil, food, water, and other materials to carrier and formation ships at sea, ensuring strong survivability and sustained combat capability. To ensure adequate supplies for maritime missions, the logistics department needs to make an accurate scientific prediction of material consumption before the mission. In this paper, a method for maritime logistics support material demand prediction based on an improved least squares support vector machine is proposed, and the feasibility and accuracy of the method are validated through various arithmetic examples and realistic scenarios, demonstrating its practical applicability and accuracy in predicting material demands.