Sabiia Seb
PortuguêsEspañolEnglish
Embrapa
        Busca avançada

Botão Atualizar


Botão Atualizar

Ordenar por: 

RelevânciaAutorTítuloAno

Imprime registros no formato resumido
Registros recuperados: 2
Primeira ... 1 ... Última
Imagem não selecionada

Imprime registro no formato completo
แบบจำลองการเจริญเติบโตและผลผลิตของถั่วเขียว โดยใช้โครงข่ายประสาทเทียม 106
Supatsorn Kumbor; Hatsachai Boonjung; Arthit Srikaew.
Most of crop modeling is mechanistic model whereas the objective of this study was to predict mungbean growth and yield by artificial neural network (ANN). The experiment was 2 varieties (SUT1 and KPS2) x 2 water levels (rainfed and irrigation) x 3 fertilizer levels (12-24-12 rate 0, 15 and 30kg./rai) factorial experiment in RCBD 4 blocks growing for 2 seasons (no rainfed in the 2nd season). Data was collected for 10 replications in each plot. Using 560 sets of data from fertilizer rate of 0 and 30 kg/rai trained the ANN model by back propagation algorithm. The input variables were variety, fertilizer, irrigations, seasonal, growing degree day, rainfall, solar radiation and day after planting. The rest of 280 sets of data (only 15 kg/rai of fertilizer)...
Tipo: Collection Palavras-chave: Mungbean; Artificial neural network; Growth models; Yield models; ถั่วเขียว; โครงข่ายประสาทเทียม; แบบจำลองการเจริญเติบโต; ผลผลิต.
Ano: 2014 URL: http://anchan.lib.ku.ac.th/agnet/handle/001/5570
Imagem não selecionada

Imprime registro no formato completo
แบบจำลองการเจริญเติบโตและผลผลิตของถั่วเขียว โดยใช้โครงข่ายประสาทเทียม 106
Supatsorn Kumbor; Hatsachai Boonjung; Arthit Srikaew.
Most of crop modeling is mechanistic model whereas the objective of this study was to predict mungbean growth and yield by artificial neural network (ANN). The experiment was 2 varieties (SUT1 and KPS2) x 2 water levels (rainfed and irrigation) x 3 fertilizer levels (12-24-12 rate 0, 15 and 30kg./rai) factorial experiment in RCBD 4 blocks growing for 2 seasons (no rainfed in the 2nd season). Data was collected for 10 replications in each plot. Using 560 sets of data from fertilizer rate of 0 and 30 kg/rai trained the ANN model by back propagation algorithm. The input variables were variety, fertilizer, irrigations, seasonal, growing degree day, rainfall, solar radiation and day after planting. The rest of 280 sets of data (only 15 kg/rai of fertilizer)...
Tipo: Collection Palavras-chave: Mungbean; Artificial neural network; Model; ถั่วเขียว; โครงข่ายประสาทเทียม; แบบจำลองโครงข่ายประสาทเทียม; ผลผลิต.
Ano: 2014 URL: http://anchan.lib.ku.ac.th/agnet/handle/001/5840
Registros recuperados: 2
Primeira ... 1 ... Última
 

Empresa Brasileira de Pesquisa Agropecuária - Embrapa
Todos os direitos reservados, conforme Lei n° 9.610
Política de Privacidade
Área restrita

Embrapa
Parque Estação Biológica - PqEB s/n°
Brasília, DF - Brasil - CEP 70770-901
Fone: (61) 3448-4433 - Fax: (61) 3448-4890 / 3448-4891 SAC: https://www.embrapa.br/fale-conosco

Valid HTML 4.01 Transitional