Dynamics Analysis and Intelligent Prediction of Aquaculture Data

Authors

Jiezhuo Zhong, 1. College of Information Science and Technology, Hainan University, Haikou 570228, China; ;
Zhigang Tu, 2. Hainan Academy of Oceam and Fisheries Sciences, Haikou 570206, China; ;
Wencai Du, 1. College of Information Science and Technology, Hainan University, Haikou 570228, China; ;
Wu Wei, 1. College of Information Science and Technology, Hainan University, Haikou 570228, China; ;3. Sanya Institute of Deep-sea Science and Engineering, Chinese Academy of Sciences, Sanya 572000, China;

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.

Recommended Citation

Zhong, Jiezhuo; Tu, Zhigang; Du, Wencai; and Wei, Wu (2020) "Dynamics Analysis and Intelligent Prediction of Aquaculture Data," Journal of System Simulation: Vol. 29: Iss. 5, Article 16.
DOI: 10.16182/j.issn1004731x.joss.201705016
Available at: https://dc-china-simulation.researchcommons.org/journal/vol29/iss5/16

First Page

1049

Revised Date

2015-07-06

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201705016

Last Page

1056

CLC

TP18

Recommended Citation

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.

DOI

10.16182/j.issn1004731x.joss.201705016