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Previsão da localização ideal de edifícios com redes neurais artificiais de autoaprendizagem

Previsão da localização ideal de edifícios com redes neurais artificiais de autoaprendizagem

SHAKEELA SHAIKH / ZIYA UL HAQUE

94,73 €
IVA incluido
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Editorial:
KS OmniScriptum Publishing
Año de edición:
2026
Materia
Ciencia, ingeniería y tecnología medioambientales
ISBN:
9786209531323
94,73 €
IVA incluido
Disponible
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A rápida urbanização e os projectos complexos levam a indústria da construção a adotar a IA e o ML para soluções mais rápidas, seguras e económicas. Neste livro de investigação, foram utilizados relatórios de investigação do solo para definir parâmetros específicos do local e foram analisados 10 casos distintos de edifícios utilizando software de análise de edifícios, cada um com rigidez de mola individual (K). Foi desenvolvida uma abordagem ML baseada em Python para prever configurações estruturais optimizadas de vários andares, com foco na força axial do pilar. O código AI-ML, composto por duas fases, identifica as entradas, gera gráficos utilizando Matplotlib v3.10.3 e compara os valores previstos com os valores reais para avaliar o MSE e o R². O pré-processamento de dados utilizou Pandas v2.0.3 e NumPy v1.26.4, enquanto os modelos de regressão linear e ANN (TensorFlow v2.16.1, sklearn v1.3.0) foram treinados numa divisão 80:20. A RNA alcançou um MSE de 0 e R² de 1, marcando uma precisão e eficiência superiores para a otimização do design estrutural.

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