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Pineda Lezama, Omar Bonerge (3)
amelec, viloria (1)Arrieta Matos, Fernanda (1)CABAS VASQUEZ, LUIS CARLOS (1)Flórez Guzman, Yasmin (1)Gaitán, Mercedes (1)Gaitán-Angulo, Mercedes (1)Hernández Palma, Hugo (1)Lozano Ayarza, Liliana Patricia (1)Martínez Galán, Zuleima del Carmen (1)... View MoreSubject
Forecast (3)
Cyclic variation (2)Multiple input multiple output (2)Support vector machines (2)Artificial Neural Networks (1)Big Data (1)Demand (1)Demanda (1)Multilayer Perceptron (1)Multilayer perceptron (1)... View MoreDate Issued2019 (2)2020 (1)Has File(s)Yes (3)

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An early warning method for agricultural products price spike based on artificial neural networks prediction 

Silva, Jesús; Gaitán-Angulo, Mercedes; Romero Borré, Jenny; Lozano Ayarza, Liliana Patricia; Pineda Lezama, Omar Bonerge; Martínez Galán, Zuleima del Carmen; Navarro Beltran, Jorge (Universidad de la Costa, 2020)
In general, the agricultural producing sector is affected by the diversity in supply, mostly from small companies, in addition to the rigidity of the demand, the territorial dispersion, the seasonality or the generation ...
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Demand forecasting method using artificial neural networks 

amelec, viloria; Arrieta Matos, Fernanda; Gaitán, Mercedes; Hernández Palma, Hugo; Flórez Guzman, Yasmin; CABAS VASQUEZ, LUIS CARLOS; Vargas Mercado, Carlos; Pineda Lezama, Omar Bonerge (Universidad de la Costa, 2019)
Based on a forecast, the decision maker can determine the capacity required to meet a certain forecast demand, as well as carry out in advance the balance of capacities in order to avoid underusing or bottlenecks. This ...
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Early warning method for the commodity prices based on artificial neural networks: SMEs case 

Silva, Jesus; MOJICA HERAZO, JULIO CESAR; Rojas Millán, Rafael Humberto; Pineda Lezama, Omar Bonerge; Morgado Gamero, W.B.; Varela Izquierdo, Noel (Procedia Computer Science, 2019)
Applications based on Artificial Neural Networks (ANN) have been developed thanks to the advance of the technological progress which has permitted the development of sales forecasting on consumer products, improving the ...

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