IFNN时变模型在建立大坝位移监控中的应用

Application of Improved Fuzzy Neural Network Technology in Dam Displacement Monitoring Model

针对时变监控模型比常规监控模型更有效且能准确进行变量分离,通过改进的模糊神经网络(IFNN)结合时变模型对陈村水库大坝的水平位移进行拟合与预测,并与BP模型做了比较。结果表明,该模型拟合及预测精度均较BP模型高,与工程实例相近,可推广应用。

Time-varying monitoring model is more effective and accurate than the conventional model of monitoring in the variable separation and has more precise physical and mechanical significance. In this article, the improved fuzzy neural network with time-varying model in fitting and forecasting of the horizontal displacement monitoring of one dam is used, and the BP model is the comparative example. According to the comparison of the final results and the actual data, the fitting and forecasting accuracy of the model which uses the improved fuzzy neural network with time-varying monitoring model is higher than the conventional model of BP ,so it can be applied to practical projects.