Debris flow volume prediction model based on back propagation neural network optimized by improved whale optimization algorithm.

ABSTRACT: Debris flow is a sudden natural disaster in mountainous areas, which seriously threatens the lives and property of nearby residents. Therefore, it is necessary to predict the volume of debris flow accurately and reliably. However, the predictions of back propagation neural networks are unstable and inaccurate due to the limited dataset. In this study, the Cubic map optimizes the initial population position of the whale optimization algorithm. Meanwhile, the adaptive weight adjustment strategy optimizes the weight value in the shrink-wrapping mechanism of the whale optimization algorithm. Then, the improved whale optimization algorithm optimizes the final weights and thresholds in the back propagation neural network. Finally, to verify the performance of the final model, sixty debris flow g

SUBMITTER: Ni B 

PROVIDER: S-EPMC11003783 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature