Dynamics Analysis and Intelligent Prediction of Aquaculture Data

doi:10.16182/j.issn1004731x.joss.201705016

Abstract

Abstract: Data analysis on environmental factors data is crucial to aquaculture, in which three significant parameters were discussed, they are temperature, PH and dissolved oxygen. Fixing some missing data and inaccurate records in the sampling process by high-order curve fitting. Meanwhile, the use of filtering method was adopted to divide systematic errors and rhythms inside parameters. Analysis from different water layers and different time suited the true environment well, which provided effective references for engineering problems. Radial Basis Function Neural Networks was well applied in tracking the parameters trend both globally and locally.

Key words: aquaculture quality, dynamic analysis, nonlinear prediction, artificial neural networks

CLC Number:

TP18

Zhong Jiezhuo, Tu Zhigang, Du Wencai, Wu Wei. Dynamics Analysis and Intelligent Prediction of Aquaculture Data[J]. Journal of System Simulation, 2017, 29(5): 1049-1056.

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