Study on resource quantity of surface water based on phase space reconstruction and neural network

• 来源期刊: 煤炭学报（英文版）
• 年，卷（期）: 2006,（1）
• 页码范围: 39-42
• 页数: 4页
• 语种: 英文

摘要

Proposed a new method to disclose the complicated non-linearity structure of the water-resource system, introducing chaos theory into the hydrology and water resources field, and combined with the chaos theory and artificial neural networks. Training data construction and networks structure were determined by the phase space reconstruction, and establishing nonlinear relationship of phase points with neural networks, the forecasting model of the resource quantity of the surface water was brought forward. The keystone of the way and the detailed arithmetic of the network training were given. The example shows that the model has highly forecasting precision.