摘要
针对神经网络洪水预报模型的结构难以确定的问题 ,应用一种在训练过程中可调整隐层神经元数的算法 ,建立了变结构神经网络洪水预报模型。该方法提供了设计面向问题的网络结构的途径 ,在网络结构设计。
In accordance with the determination of structure of ANN for flood forecasting, this paper applied an algorithm that can modify the structure during the process of learning to build a ANN model for short term flood forecasting. This algorithm provides a way to design the structure of problem oriented neural network. The result shows that it is practical in the design of ANN and improves flood forecasting accuracy.
出处
《水电能源科学》
2002年第1期12-14,共3页
Water Resources and Power
基金
国家自然科学基金重大项目 (5 0 0 9962 0 )
武汉大学青年科学基金项目资助
关键词
洪水预报
变结构神经网络
变结构算法
flood forecasting
variable structure neural network
variable structure algorithm