• DocumentCode
    2816743
  • Title

    Combining Neural Networks and Genetic Algorithms to Predict and to Maximize Lemon Grass Oil Production

  • Author

    Mishra, K.K. ; Singh, Brajesh Kumar ; Punhani, Akash ; Singh, Uma

  • Author_Institution
    Fac. of Eng. & Technol., Dept. of Comput. Sci. & Eng., Raja Balwant Singh Coll., Agra, India
  • Volume
    1
  • fYear
    2009
  • fDate
    24-26 April 2009
  • Firstpage
    297
  • Lastpage
    299
  • Abstract
    In this paper, a combination of neural networks and genetic algorithms have been used to predict and maximize lemon grass oil production. The best combinations could be assessed for N+P2O5+ZnSO4 (Kgha-1) as 89.03 + 60.00 + 40.65, 114.84 + 60.00+33.39, 120.00 + 54.84 + 42.10 and 120.00 + 60.00+45.00 respectively for maximum oil production. Contribution of each nutrient combinations is also identified.
  • Keywords
    agricultural engineering; crops; essential oils; fertilisers; genetic algorithms; neural nets; production engineering computing; genetic algorithms; lemon grass oil production; neural networks; Counting circuits; Crops; Fertilizers; Genetic algorithms; Genetic engineering; Genetic mutations; Irrigation; Neural networks; Optimized production technology; Petroleum; Genetic algorithm; back propagation neural network; fertilizers; oil production;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Sciences and Optimization, 2009. CSO 2009. International Joint Conference on
  • Conference_Location
    Sanya, Hainan
  • Print_ISBN
    978-0-7695-3605-7
  • Type

    conf

  • DOI
    10.1109/CSO.2009.158
  • Filename
    5193699
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2816743