2023
DOI: 10.21203/rs.3.rs-2877920/v1
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Water yield of mine analysis and prediction method based on EEMD-PSO- ELM-LSTM model

Abstract: In view of the complexity of mine water inflow data analysis and the uncertainty of prediction and prediction and other key issues, according to the data characteristics of metal mine water inflow, a method of mine water inflow analysis and prediction based on EEMD PSO-ELM-LSTM is proposed by applying the phase space reconstruction idea and the fusion modeling concept. Taking the monthly average water inflow of JIAOJIA Gold Mine in China from January 2014 to October 2021 as an example. Firstly, the Ensemble Em… Show more

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“…He posits that employing Empirical Mode Decomposition (EMD) offers a viable solution to this problem, providing an effective strategy for addressing prediction latency in critical applications such as soil moisture. Furthermore, Zhao et al [51] demonstrated that Ensemble Empirical Mode Decomposition (EEMD) captures periodic changes and environmental conditions. When combined with the attention mechanism, it significantly enhances predictive performance and effectively mitigates prediction lag.…”
Section: Discussionmentioning
confidence: 99%
“…He posits that employing Empirical Mode Decomposition (EMD) offers a viable solution to this problem, providing an effective strategy for addressing prediction latency in critical applications such as soil moisture. Furthermore, Zhao et al [51] demonstrated that Ensemble Empirical Mode Decomposition (EEMD) captures periodic changes and environmental conditions. When combined with the attention mechanism, it significantly enhances predictive performance and effectively mitigates prediction lag.…”
Section: Discussionmentioning
confidence: 99%