Application of artificial intelligence to estimate phycocyanin pigment concentration using water quality data: a comparative study

Application of artificial intelligence to estimate phycocyanin pigment concentration using water quality data: a comparative study

Abstract In the present investigation, the usefulness and capabilities of four artificial intelligence (AI) models, namely feedforward neural networks (FFNNs), gene expression programming (GEP), adaptive neuro-fuzzy inference system with grid partition (ANFIS-GP) and adaptive neuro-fuzzy inference s...

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Bibliographic Details
Main Authors: Salim Heddam, Hadi Sanikhani, Ozgur Kisi
Format: Article
Language:English
Published: SpringerOpen 2019-09-01
Series:Applied Water Science
Subjects:
Modeling
Phycocyanin concentration
Feedforward neural networks
Gene expression programming
Adaptive neuro-fuzzy inference system
Grid partition
Online Access:http://link.springer.com/article/10.1007/s13201-019-1044-3

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http://link.springer.com/article/10.1007/s13201-019-1044-3

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