Gene Expression Programming-Fuzzy Logic Method for Crop Type Classification

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{conf/icgec/OmkarRSBA12,
  author =       "S. N. Omkar and Nikhil Ramaswamy and 
                 J. Senthilnath and S. Bharath and N. S. Anuradha",
  title =        "Gene Expression Programming-Fuzzy Logic Method for
                 Crop Type Classification",
  booktitle =    "Sixth International Conference on Genetic and
                 Evolutionary Computing (ICGEC 2012)",
  year =         "2012",
  pages =        "136--139",
  address =      "Kitakushu",
  month =        "25-28 " # aug,
  publisher =    "IEEE",
  keywords =     "genetic algorithms, genetic programming, gene
                 expression programming",
  isbn13 =       "978-1-4673-2138-9",
  URL =          "http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6451318",
  DOI =          "doi:10.1109/ICGEC.2012.97",
  bibsource =    "DBLP,
                 http://dblp.uni-trier.de/db/conf/icgec/icgec2012.html#OmkarRSBA12",
  size =         "4 pages",
  abstract =     "Crop type classification using remote sensing data
                 plays a vital role in planning cultivation activities
                 and for optimal usage of the available fertile land.
                 Thus a reliable and precise classification of
                 agricultural crops can help improve agricultural
                 productivity. Hence in this paper a gene expression
                 programming based fuzzy logic approach for multi-class
                 crop classification using Multispectral satellite image
                 is proposed. the purpose of this work is to use the
                 optimisation capabilities of GEP for tuning the fuzzy
                 membership functions. the capabilities of GEP as a
                 classifier is also studied. the proposed method is
                 compared to Bayesian and Maximum likelihood classifier
                 in terms of performance evaluation. from the results we
                 can conclude that the proposed method is effective for
                 classification.",
  notes =        "also known as \cite{6457194}",
}

Genetic Programming entries for S N Omkar Nikhil Ramaswamy J Senthilnath S Bharath N S Anuradha

Citations