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Data · dataset · 2026

Data of SSA-ELM Prediction Model for Roadside Support Stress in No-Pillar Mining

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Description

Aiming at the problem that the complex stress evolution of roadside walls in no-pillar coal mining makes it difficult to accurately judge the wall state, a mining-induced stress response database was constructed through FLAC3D numerical simulation, and an intelligent stress prediction model based on the Sparrow Search Algorithm optimized Extreme Learning Machine (SSA-ELM) was established. The parameters used for model input in the database include: mining distance, wall width, burial depth, roadway width, position, wall height, strike length, and dip length.

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Provenance · 1 source records, 13 field assertions
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ScienceDB10.57760/sciencedb.3693512 d agoJSON v1
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