基于混沌优化模糊神经网络的大坝安全监测模型

Chaos Optimization-based Fuzzy Neural Network Model for Dam Safety Monitoring

大坝监测数据分析和大坝监控预测模型的难点在于监测数据的效应量和影响量之间的高度非线性关系,传统监测模型的非线性分析能力欠缺。在充分利用模糊神经网络的模糊推理能力、处理众多影响因素能力和解决复杂非线性问题能力的基础上,结合混沌优化算法的全局搜索能力,建立了基于混沌优化的模糊神经网络模型。对某拱坝变形进行了拟合和预测,计算结果与实测值吻合良好。

The difficulty in dam monitoring data analysis and monitoring and forecasting model is the determination of the complex nonlinear relationship between the effect quantity and influence quantity; the ability of traditional monitoring models to solve the non-linear problem is deficient. In this paper, on the basis of combining fuzzy neural network with chaos optimization, the fuzzy reasoning ability, various influencing factors processing ability and non-linear problem-solving ability of the fuzzy neural network and the global searching ability of chaos optimization are all made full use of, and the fuzzy neural network （FNN） model based on chaos optimization is built. The fitting and forecasting of deformation of an arch dam indicates that the fitting and forecasting data obtained by this model is in good agreement with the measured data.