Prediction of bow blow concentration of trailing suction hopper dredger by LSTM with stacking fusion

Abstract

During the bow blowing construction of a trailing suction dredger, the concentration meter and flow rate meter can instantly reflect the transmission situation of the mud sand mixture in the pipeline, which is the most concerned fluid parameter for construction personnel. To ensure the high efficiency and low energy consumption of the bow blowing operation, this paper proposes an LSTM trailing suction dredger bow blowing concentration prediction model that integrates Stacking. This model fully considers the dynamic characteristics of the fluid and combines machine learning advantages to achieve higher concentration prediction accuracy, which has practical application value.