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Analysis of Andean blackberry (Rubus glaucus) production models obtained by means of artificial neural networks exploiting information collected by small-scale growers in Colombia and publicly available meteorological data

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Input relevance analysis, Publicly available meteorological data, Self-Organizing Maps, Multilayer perceptron, Artificial neural networks, Andean blackberry, Small-scale growers, CROSS-VALIDATION, PREDICTION

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Chicago
Jimenez Rodas, Daniel, James Cock, Héctor F Satizábal, Miguel A Barreto, Andrés Pérez-Uribe, Andy Jarvis, and Patrick Van Damme. 2009. “Analysis of Andean Blackberry (Rubus Glaucus) Production Models Obtained by Means of Artificial Neural Networks Exploiting Information Collected by Small-scale Growers in Colombia and Publicly Available Meteorological Data.” Computers and Electronics in Agriculture 69 (2): 198–208.
APA
Jimenez Rodas, D., Cock, J., Satizábal, H. F., Barreto, M. A., Pérez-Uribe, A., Jarvis, A., & Van Damme, P. (2009). Analysis of Andean blackberry (Rubus glaucus) production models obtained by means of artificial neural networks exploiting information collected by small-scale growers in Colombia and publicly available meteorological data. COMPUTERS AND ELECTRONICS IN AGRICULTURE, 69(2), 198–208.
Vancouver
1.
Jimenez Rodas D, Cock J, Satizábal HF, Barreto MA, Pérez-Uribe A, Jarvis A, et al. Analysis of Andean blackberry (Rubus glaucus) production models obtained by means of artificial neural networks exploiting information collected by small-scale growers in Colombia and publicly available meteorological data. COMPUTERS AND ELECTRONICS IN AGRICULTURE. 2009;69(2):198–208.
MLA
Jimenez Rodas, Daniel, James Cock, Héctor F Satizábal, et al. “Analysis of Andean Blackberry (Rubus Glaucus) Production Models Obtained by Means of Artificial Neural Networks Exploiting Information Collected by Small-scale Growers in Colombia and Publicly Available Meteorological Data.” COMPUTERS AND ELECTRONICS IN AGRICULTURE 69.2 (2009): 198–208. Print.
@article{1078499,
  author       = {Jimenez Rodas, Daniel and Cock, James and Satiz{\'a}bal, H{\'e}ctor F and Barreto, Miguel A and P{\'e}rez-Uribe, Andr{\'e}s and Jarvis, Andy and Van Damme, Patrick},
  issn         = {0168-1699},
  journal      = {COMPUTERS AND ELECTRONICS IN AGRICULTURE},
  keyword      = {Input relevance analysis,Publicly available meteorological data,Self-Organizing Maps,Multilayer perceptron,Artificial neural networks,Andean blackberry,Small-scale growers,CROSS-VALIDATION,PREDICTION},
  language     = {eng},
  number       = {2},
  pages        = {198--208},
  title        = {Analysis of Andean blackberry (Rubus glaucus) production models obtained by means of artificial neural networks exploiting information collected by small-scale growers in Colombia and publicly available meteorological data},
  url          = {http://dx.doi.org/10.1016/j.compag.2009.08.008},
  volume       = {69},
  year         = {2009},
}

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