Fast Identification Method of Mine Water Source Based on Laser-Induced Fluorescence Technology and Optimized LSTM
نویسندگان
چکیده
There is a great threat to the production safety of coal mines caused by mine water disasters. Traditional identification methods are not adapted efficiency today’s mining and do offer advantage accurate detection in real-time. In this study, Mayfly Algorithm (MA) was used optimize Long Short-Term Memory (LSTM) network, combined with laser-induced fluorescence technology, apply it sources for prevention disasters post-disaster relief work. Taking sandstone goaf as original samples, five mixed samples were also prepared mixing different proportions, giving total seven be tested. Laser-induced technology obtain spectral data then Linear Discriminant Analysis (LDA) dimensionality reduction algorithm Principal Component (PCA) reduce dimensions data. Then, three architectures, including LSTM, GA-LSTM (optimization LSTM genetic algorithm) MA-LSTM designed identify sources. Finally, from results’ analysis, performs best many aspects after PCA has effect. These results supported feasibility novel method.
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ژورنال
عنوان ژورنال: Water
سال: 2023
ISSN: ['2073-4441']
DOI: https://doi.org/10.3390/w15040701