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Prognozowanie optymalnej lokalizacji budynku z wykorzystaniem samouczącej się sieci neuronowej
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ISBN10: 6209528767
ISBN13: 9786209528767
Publisher: Wydawnictwo Nasza Wiedza
Published: Jan 31 2026
Pages: 92
Weight: 0.30
Height: 0.22 Width: 6.00 Depth: 9.00
Language: Polish
ISBN13: 9786209528767
Publisher: Wydawnictwo Nasza Wiedza
Published: Jan 31 2026
Pages: 92
Weight: 0.30
Height: 0.22 Width: 6.00 Depth: 9.00
Language: Polish
Szybka urbanizacja i zlożone projekty sklaniają branżę budowlaną do stosowania sztucznej inteligencji i uczenia maszynowego w celu uzyskania szybszych, bezpieczniejszych i bardziej oplacalnych rozwiązań. W tej książce badawczej wykorzystano raporty z badań gleby do zdefiniowania parametrów specyficznych dla danego miejsca, a 10 różnych przypadków budynków przeanalizowano za pomocą oprogramowania do analizy budynków, każdy z indywidualną sztywnością sprężyny (K). Podejście ML oparte na Pythonie zostalo opracowane w celu przewidywania optymalnych wielopiętrowych konfiguracji strukturalnych, koncentrując się na sile osiowej slupa. Kod AI-ML, skladający się z dwóch etapów, identyfikuje dane wejściowe, generuje wykresy przy użyciu Matplotlib v3.10.3 i porównuje wartości przewidywane z rzeczywistymi w celu oceny MSE i R . Do wstępnego przetwarzania danych wykorzystano Pandas v2.0.3 i NumPy v1.26.4, a modele regresji liniowej i sieci neuronowej (TensorFlow v2.16.1, sklearn v1.3.0) zostaly wytrenowane w podziale 80:20. Siec ANN osiągnęla MSE równe 0 i R równe 1, co oznacza doskonalą dokladnośc i wydajnośc optymalizacji projektu konstrukcyjnego.
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