A combined model of dissolved oxygen prediction in the pond based on multiple-factor analysis and multi-scale feature extraction-Reference-Cited by-同舟云学术

A combined model of dissolved oxygen prediction in the pond based on multiple-factor analysis and multi-scale feature extraction

Published:2019-02 Issue: Volume:84 Page:50-59
ISSN:0144-8609
Container-title:Aquacultural Engineering
language:en
Short-container-title:Aquacultural Engineering

Author:

Cao Weijian,Huan Juan,Liu Chen,Qin Yilin,Wu Fan

Funder

Chinese National Natural Science Foundation

2016 annual Liyang key research and development project

Publisher

Elsevier BV

Subject

Aquatic Science

Reference31 articles.

1. Prediction of dissolved oxygen in Surma River by biochemical oxygen demand and chemical oxygen demand using the artificial neural networks (ANNs);Ahmed;J. King Saud Univ. – Eng. Sci.,2014

2. Application of adaptive neuro-fuzzy inference system (ANFIS) to estimate the biochemical oxygen demand (BOD) of Surma River;Ahmed;J. King Saud Univ. – Eng. Sci.,2015

3. Application of eemd and neural network in stress prediction of anchor bolt;Bian;Int. J. Comput. Appl. Technol.,2018

4. Application of artificial neural networks to the forecasting of dissolved oxygen content in the hungarian section of the river danube;Csábrági;Ecol. Eng.,2017

5. A closer look on spatiotemporal variations of dissolved oxygen in waste stabilization ponds using mixed models;Ho;Water,2018

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