Flood Prediction Method Based on Deep Belief Extreme Learning Machine and Convolution Optimization Algorithm
The ICOA-DBN-ELM model based on deep belief network(DBN),extreme learning machine(ELM)and improved convolution optimization algorithm(ICOA)is proposed to solve the problems of flood prediction difficulty and unsatisfactory accuracy caused by large flood peak,short convolution time and complex basin topography.The daily run-off data of the Beidao hydrological station in the upper reaches of the Wei River from 2006 to 2020 were used as input da-ta,and the model was compared with BP,ELM,DBN-BP,DBN-ELM and COA-DBN-ELM models.The results show that the established ICOA-DBN-ELM model has better prediction accuracy,and has a good application prospect in the field of flood prediction.
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