基于GIS与ANN的金川二矿地表移动预测

利用金川二矿区多年的GPS监测数据，探讨了GIS与人工神经网络技术相结合进行地表移动定量预测的方法和思路。借助Avenue语言，实现了在GIS平台下进行地表移动神经网络预测的整个过程，包括样本设计、网络设计与训练、网络测试与网络预测等；其中，数据处理、测试结果对比和预测结果分析由GIS软件完成，采用VB调用Matlab6.5实现Elman神经网络预测模型，并通过Avenue编程将其集成到GIS系统中。研究结果表明，利用GIS支持下的神经网络模型对地表移动进行预测，具有理论上的可行性和现实意义，说明GIS和人工神经网络技术在开采沉陷预计领域中具有广阔的应用前景。

Ground Movement Prediction of No.2 Nickel Mine Area in Jinchuan Based on GIS and ANN

Based on GPS monitoring data on No.2 Nickel Mine Area in Jinchuan, a new idea of quantitative prediction of ground surface movement by means of GIS and ANN(Artificial Neural Network) was put forward and the specific method was given.The whole process of ground surface movement prediction based on ANN may be carried out in GIS platform by Avenue programming, including designing data mode, designing and training network framework, testing network framework, forecasting by network, and so on.Such works as data processing, contrasting testing results and analysing forecasting results were achieved by GIS.The Elman ANN prediction model was realized by the technique of Matlab 6.5 program with VB6.0, which was integrated in GIS by Avenue programming.The results stated that the ANN prediction model supported by GIS had a theoretical feasibility and realistic significance in predicting ground surface movement, and GIS and ANN had a wide application prospect in prediction of exploitation subsidence.