Research on Settlement Prediction of Small Water Conservancy Project based on ELM Model Optimized by Genetic Algorithm

摘要

To find suitable for small water conservancy engineering standard method for prediction of subsidence. This paper based on the genetic algorithm GA optimization extreme learning machine, three different ELM model activation function. From this, six computational models are obtained. According to the input of groundwater dynamic changes, precipitation, temperature and soil four indicators of the two kinds of input combinations, a total of 12 kinds of model input. It’s concluded that the optimal settlement prediction model, the results showed that: Ga-ELM_(sin)model shows high accuracy, and genetic algorithm can improve the calculation accuracy of ELM model. Groundwater dynamics is the main factor affecting settlement.