COAL FLOW PREDICTION METHOD BASED ON IMPROVED HONEY BADGER ALGORITHM, DEVICE, MEDIUM AND PRODUCT

Abstract

Disclosed are a coal flow prediction method based on an improved honey badger algorithm, a device, a medium and a product. The improved honey badger algorithm is used to optimize random forest models, and the improved honey badger algorithm is based on a standard honey badger optimization algorithm. Sine chaotic mapping is introduced to perform population initialization, a feedback sharing strategy is introduced to update individual positions after a mining stage or a honeycreeper stage, and a Levy flight strategy is introduced to update a position of a current optimal honey badger individual after the feedback sharing stage is completed. The improved honey badger algorithm enhances global search ability of a standard honey badger algorithm. According to the present invention, parameters of the random forest models are optimized by the improved honey badger algorithm, and prediction accuracy of the random forest models on coal flow is enhanced.

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