A Bayesian structural model for predicting algal blooms-Reference-Cited by-同舟云学术

A Bayesian structural model for predicting algal blooms

Published:2019-04-10 Issue:8 Volume:38 Page:788-802
ISSN:0277-6693
Container-title:Journal of Forecasting
language:en
Short-container-title:Journal of Forecasting

Author:

Sun Xinyu¹^ORCID,Liu Tao¹,Wang Jiayin²

Affiliation:

1. School of ManagementKey Lab of the Ministry of Education for Process Control and Efficiency Engineering, Xi'an Jiaotong University Xi'an Shannxi China

2. School of the Electronic and Information EngineeringXi'an Jiaotong University Xi'an Shannxi China

Funder

Fundamental Research Funds for the Central Universities

National Natural Science Foundation of China

Natural Science Foundation of Shaanxi Province

Publisher

Wiley

Subject

Management Science and Operations Research,Statistics, Probability and Uncertainty,Strategy and Management,Computer Science Applications,Modeling and Simulation

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/for.2583

Reference43 articles.

1. Identification of the parameters describing primary production from continuous oxygen signals

2. Detecting the red tide algal blooms from satellite ocean color observations in optically complex Northeast-Asia Coastal waters

3. A high resolution hydrodynamic model system suitable for novel harmful algal bloom modelling in areas of complex coastline and topography

4. Circulation and environmental conditions during a toxigenic Pseudo-nitzschia australis bloom in the Santa Barbara Channel, California

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