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• W241291220 startingPage "170" @default.
• W241291220 abstract "This study was conducted in order to model energy consumption and greenhouse gas emissions for peanut production in Guilan province of Iran using artificial neural network (ANN). Also, the multi-objective genetic algorithm was used for optimization of energy inputs and GHG emissions in the region. Data were randomly collected from 120 farms in Astaneh Ashrafiyeh city with face to face questionnaire method. The results illustrated that the total energy consumption and the average yield were calculated as 19248.04 MJ ha-1 and 3488.39 kg ha -1 , respectively. Moreover, the results showed that the share of chemical fertilizers (mainly nitrogen) and diesel fuel energy to the total energy input were the highest. Also, the energy used efficiency ratio calculated as 4.53. The results of GHG emissions analysis showed the total GHG emissions were 571.18 kgCO2eq. ha -1 and the diesel fuel has the main reasonable of GHG emissions in peanut production. In this study, several direct and indirect factors have been identified to create a model based on ANN to predict energy use and GHG emissions in peanut production. The ANN model with 9-22-2 structure was capable of predicting the peanut yield and GHG emissions. Moreover, the results of the best topology showed that R 2 was 0.994 and 0.999, RMSE was 0.076 and 0.003 and MAPE was 0.174 and 0.009 for peanut yield and GHG emissions, respectively. The results of optimization indicated the total energy consumption and GHG emissions generation was calculated about 6888 MJ ha -1 and 159.08 kgCO2eq. ha -1 , respectively. The total GHG emissions reduction was found to be 412.09 kgCO2eq. ha -1 in optimal generation toward present farms." @default.
• W241291220 created "2016-06-24" @default.
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• W241291220 date "2014-04-11" @default.
• W241291220 modified "2023-09-23" @default.
• W241291220 title "Applying artificial neural networks and multi-objective genetic algorithm to modeling and optimization of energy inputs and greenhouse gas emissions for peanut production" @default.
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• W241291220 doi "https://doi.org/10.12692/ijb/4.7.170-183" @default.
• W241291220 hasPublicationYear "2014" @default.
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