2019 Eleventh International Conference on Advanced Computational Intelligence (ICACI) 2019
DOI: 10.1109/icaci.2019.8778465
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Parameter Identification, Verification and Simulation of the CSD Transport Process

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“…Excavation productivity refers to the average volume of slurry excavated by cutter head per unit time, which is mainly affected by factors such as cutter size, soil type, and motor power of the dredging ship. Pipeline transportation productivity refers to the average volume of slurry transported through the pipeline per unit time, determined primarily by the characteristics of the pipeline and the slurry (Li et al , 2019a, b). Tam et al (2002) used artificial neural networks model to predict the excavator productivity and got a promising result.…”
Section: Productivity Influencing Factors and Machine-learning Methodsmentioning
confidence: 99%
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“…Excavation productivity refers to the average volume of slurry excavated by cutter head per unit time, which is mainly affected by factors such as cutter size, soil type, and motor power of the dredging ship. Pipeline transportation productivity refers to the average volume of slurry transported through the pipeline per unit time, determined primarily by the characteristics of the pipeline and the slurry (Li et al , 2019a, b). Tam et al (2002) used artificial neural networks model to predict the excavator productivity and got a promising result.…”
Section: Productivity Influencing Factors and Machine-learning Methodsmentioning
confidence: 99%
“…A non-linear productivity optimization model based on Lagrange algorithm was also proposed and verified. Li et al (2019a, b) used Kalman Filter to decompose monitoring data, simulated the pipeline transportation of CSD, and established a mathematical model of pump and pipeline for improving dredging productivity. Yang et al (2015) established a backpropagation neural network (BPNN) model to predict CSD productivity based on three influencing factors: swing speed, the velocity of the hydraulic pipeline transportation, and the work-pressure of the cutter.…”
Section: Literature Reviewmentioning
confidence: 99%