将小波理论与神经网络理论相结合,建立了小波网络模型,并应用于工程实例。它避免了BP神经网络结构设计的盲目性和局部最优等非线性优化问题,大大简化了训练,具有较强的函数学习能力和推广能力。实例计算结果表明,小波网络模型具有比BP神经网络收敛速度快、预测精度高等特点,因而具有广阔的应用前景。 Combining wavelet theory with neural network theory, a wavelet network model is established and applied to engineering examples. It avoids the blindness of the BP neural network structure design and local optimization and other nonlinear optimization problems, greatly simplifying the training, has a strong function of learning and promotion capabilities. The calculation example shows that the wavelet network model has faster convergence rate and higher prediction accuracy than BP neural network, so it has a broad application prospect.