Aplicação Da Técnica de Redes Neuronais Artificiais
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Aplicação Da Técnica de Redes Neuronais Artificiais

Aplicação Da Técnica de Redes Neuronais Artificiais


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About the Book

A precipitação é um parâmetro muito importante no modelo hidrológico. Foram desenvolvidas muitas técnicas e modelos para a previsão da precipitação. Este estudo apresenta um método de previsão da precipitação através do desenvolvimento de um modelo baseado em RNA que utiliza as principais variáveis meteorológicas, tais como a temperatura de bolbo seco, a temperatura de bolbo húmido, a humidade relativa, a evaporação da panela e a pressão de vapor como entradas, enquanto a precipitação é o resultado pretendido. Como parte dos procedimentos de desenvolvimento do modelo ANN, os conjuntos de dados de 11956 dados na área de estudo foram divididos em duas partes, com 70% dos conjuntos de dados completos utilizados como dados de treino, enquanto os restantes 30% foram utilizados como dados de teste e validação. O modelo proposto foi capaz de prever valores com resultados adequados. Para a avaliação dos resultados e da capacidade dos modelos de prognóstico desenvolvidos, foram utilizados índices estatísticos adequados, como o coeficiente de determinação (R2), a raiz do erro quadrático médio (RMSE), o erro quadrático médio (MSE), a eficiência de Nash-Sutcliffe (EF), os critérios de informação de Akaike (AIC) e os critérios de informação bayesianos (BIC). Os resultados desta análise mostraram que o modelo ANN 5-5-3-1 fornece resultados satisfatórios com base em índices estatísticos.


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Product Details
  • ISBN-13: 9786206369516
  • Publisher: KS Omniscriptum Publishing
  • Binding: Paperback
  • Language: Portuguese
  • Returnable: N
  • Weight: 177 gr
  • ISBN-10: 620636951X
  • Publisher Date: 22 Aug 2023
  • Height: 229 mm
  • No of Pages: 80
  • Spine Width: 5 mm
  • Width: 152 mm


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