ID:
publications-738
Type:
PEER REVIEWED ARTICLE
Year:
2015
Authors:
Patricio Lopez-Exposito , Angeles Blanco Suarez , Carlos Negro
Title:
Estimation of Chlamydomonas reinhardtii biomass concentration from chord length distribution data
Venue/Journal:
DOI:
10.1007/s10811-015-0749-4
Research type:
AI & Machine Learning
Water System:
Uncategorized
Technical Focus:
Abstract:
Abstract A novel method to estimate the concentration of Chlamydomonas reinhardtii biomass was developed. The method employs the chord length distribution information gathered by means of a focused beam reflectance probe immersed in the culture sample and processes the data through a feedforward multilayer perceptron. The multilayer perceptron architecture was systematically optimised through the application of a simulated annealing algorithm. The method developed can predict the concentration of microalgae with acceptable accuracy and, with further development, it could be implemented online to monitor the aggregation status and biomass concentration of microalgal cultures.
Link with Projects:
280756
Link with Tools:
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