Analysing the accuracy of machine learning techniques to develop an integrated influent time series model: case study of a sewage treatment plant, Malaysia
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Title
Analysing the accuracy of machine learning techniques to develop an integrated influent time series model: case study of a sewage treatment plant, Malaysia
Authors
Keywords
Time series model, Influent, ARIMA, Support vector machine, Recurrent neural network, Integrated SVM-NAR model
Journal
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
Volume 25, Issue 12, Pages 12139-12149
Publisher
Springer Nature
Online
2018-02-17
DOI
10.1007/s11356-018-1438-z
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