Online forecasting chlorophyll a concentrations by an auto-regressive integrated moving average model: Feasibilities and potentials
- 1 March 2015
- journal article
- Published by Elsevier in Harmful Algae
- Vol. 43, 58-65
- https://doi.org/10.1016/j.hal.2015.01.002
Abstract
No abstract availableKeywords
Funding Information
- National Natural Science Foundation of China (51425902, 51279196)
This publication has 35 references indexed in Scilit:
- A hybrid neural network model for cyanobacteria bloom in Dianchi LakeProcedia Environmental Sciences, 2010
- Controlling harmful cyanobacterial blooms in a hyper-eutrophic lake (Lake Taihu, China): The need for a dual nutrient (N & P) management strategyPublished by Elsevier ,2010
- A hybrid neural network and ARIMA model for water quality time series predictionPublished by Elsevier ,2009
- The extended Kalman filter for forecast of algal bloom dynamicsWater Research, 2009
- The effects of temperature and nutrients on the growth and dynamics of toxic and non-toxic strains of Microcystis during cyanobacteria bloomsPublished by Elsevier ,2009
- Doing Battle With the Green Monster of Taihu LakeScience, 2007
- Modeling the influence of nutrients, turbulence and grazing on Pfiesteria population dynamicsHarmful Algae, 2006
- Turbulence, watermass stratification and harmful algal blooms: an alternative view and frontal zones as “pelagic seed banks”Harmful Algae, 2002
- Transient dynamics and persistence of ecological systemsEcology Letters, 2001
- How Many Clusters? Which Clustering Method? Answers Via Model-Based Cluster AnalysisThe Computer Journal, 1998