Title :
Intelligent Modeling and Predicting Investigation of Sound Velocity of Marine Sediments
Author :
Luo, Zhonghui ; Lu, Bo ; Li, Yuzhong ; Liu, Can
Author_Institution :
Sch. of Mechatron. Eng., Guangdong Polytech. Normal Univ., Guangzhou, China
fDate :
Nov. 30 2009-Dec. 1 2009
Abstract :
Physical and mechanical parameters of marine sediment are correlated to sound velocity. At present, there is some deficiency in sound velocity prediction equation with the help of regression fitting method. So it is difficult to obtain sound velocity prediction equation with more than three parameters. This paper applies artificial intelligent method to build a neural network model of multi-parameter sound velocity prediction. The investigation indicates that prediction error of two-parameter-neural-network-model is smaller than the corresponding two-parameter-regression-model, prediction accuracy of which is lower than three-parameter-neural-network-model. This research finding is established as a new way to predict sound velocity of marine sediment.
Keywords :
acoustic wave velocity; artificial intelligence; marine engineering; neural nets; regression analysis; sediments; artificial intelligent method; marine sediments; multiparameter sound velocity prediction equation; neural network model; regression fitting method; Acoustical engineering; Artificial intelligence; Artificial neural networks; Biological system modeling; Biology computing; Equations; Neural networks; Oceans; Predictive models; Sediments; investigation of sound; marine sediment; modeling and prediction; neural network;
Conference_Titel :
Knowledge Acquisition and Modeling, 2009. KAM '09. Second International Symposium on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3888-4
DOI :
10.1109/KAM.2009.155