- author = "S. Vanitha and C. Sivapragasam and N. V. N. Nampoothiri",
- title = "Modeling of Dissolved Oxygen Using Genetic Programming Approach",
- booktitle = "International Conference on Theoretical Computer Science and Discrete Mathematics",
- year = "2016",
- editor = "S. Arumugam and Jay Bagga and Lowell W. Beineke and B. S. Panda",
- volume = "10398",
- series = "Lecture Notes in Computer Science",
- pages = "445--452",
- address = "Krishnankoil, India",
- month = "19-21 " # dec,
- publisher = "Springer",
- keywords = "genetic algorithms, genetic programming, dissolved oxygen, mathematical modelling",
- bibsource = "DBLP, http://dblp.uni-trier.de/db/conf/ictcsdm/ictcsdm2016.html#VanithaSN16",
- isbn13 = "978-3-319-64419-6",
-
DOI = "
doi:10.1007/978-3-319-64419-6_56",
- size = "8 pages",
- abstract = "Genetic Programming (GP) based modelling is suggested for modelling the variation of Dissolved Oxygen (DO) under controlled conditions in the presence and absence of toxicant. The results indicated that GP is able to evolve robust physically meaningful models even with small dataset by selecting the most relevant functions from the set of functions given for the modelling. It is interesting to note that the evolved models clearly reflect the underlying non-linearity of the process distinctly for both the case studies.",
-
notes = "Vanitha Sankararajan
Also known as \cite{conf/ictcsdm/VanithaSN16}",
