Aiming at the limitations of BPNN in the application of 3D sound velocity field modeling,such as low prediction ac-curacy,easy to fall into the local optimum,and weak interpretability,a method of the thermohaline field modeling based on BPNNs is proposed,and a sound velocity hierarchical modeling scheme is designed jointly with the empirical equation of sound velocity.Meanwhile,the BPNN function and architecture are improved and optimized by introducing an adaptive particle swarm optimization algorithm to improve the accuracy of the thermohaline field modeling.Experiments on the modeling per-formance of the proposed algorithm are conducted using BOA_Argo grid data in the central region of the South China Sea.The results show that the algorithm proposed in this paper can fully reflect the physical properties of the ocean sound velocity field,with higher modeling accuracy and robustness than traditional algorithms,and with excellent stability and reliability.
关键词
三维声速场/反向传播神经网络/粒子群优化算法/BOA_Argo网格数据
Key words
3D sound velocity field/back propagation neural network/particle swarm optimization algorithm/BOA_Argo grid data
维普
万方数据