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
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;
Conference_Titel :
Computational Sciences and Optimization, 2009. CSO 2009. International Joint Conference on
Conference_Location :
Sanya, Hainan
Print_ISBN :
978-0-7695-3605-7
DOI :
10.1109/CSO.2009.158
