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Aiming at the problem of low node positioning accuracy caused by fewer anchor nodes and large iteration errors in underwater wireless sensor networks, an underwater three-dimensional node positioning algorithm based on improved weighted least squares support vector machine is proposed.The algorithm divides the underwater three-dimensional space into several cubes, and uses the distance vector between the anchor node and the grid intersection as the training set for training.Use the classification method of multi-class pattern recognition for classification.The distance vector from the unknown node to the anchor node will be used as the test set to determine the node coordinates.By introducing weighted ideas and multi-category pattern recognition classification methods, the robustness of machine learning algorithms is increased and the number of classifications is reduced, so as to achieve underwater 3D node prediction and positioning. Simulation results show that the algorithm can maintain high positioning accuracy even in underwater areas with fewer anchor nodes and larger network areas.