A hybrid PSO optimized SVM-based model for predicting a successful growth cycle of the \textit{Spirulina platensis} from raceway experiments data

DOI10.1016/J.CAM.2015.01.009zbMath1329.92105OpenAlexW2085554264MaRDI QIDQ491044

Yong-Cai Geng, Sumit K. Garg

Publication date: 24 August 2015

Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cam.2015.01.009

zbMATH Keywords

particle swarm optimization (PSO)hyperparameter selectionsupport vector machines (SVMs)\textit{Spirulina platensis}chlorophyll a monitoring

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Population dynamics (general) (92D25) Ecology (92D40) Cell biology (92C37) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20)

Related Items (4)

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Uses Software

• LIBSVM

Cites Work

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• Support vector machines and neural networks used to evaluate paper manufactured using \textit{Eucalyptus globulus}
• Creating a quality map of a slate deposit using support vector machines
• Differential evolution -- a simple and efficient heuristic for global optimization over continuous spaces
• Support-vector networks
• Support vector machines: theory and applications.
• Cross-Validation of Regression Models
• Support Vector Machines

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