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Explores the application potentials with single-objective optimization, multiple objective optimizations, supervised learning, unsupervised learning and deep learning in architectural fields. This study focuses on developing an optimization workflow for global structural form-finding and geometry morphologies.

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Deep-Machine-Learning-In-Architecture-Application

Explores the application potentials with single-objective optimization, multiple objective optimizations, supervised learning, unsupervised learning and deep learning in architectural fields. This study focuses on developing an optimization workflow for global structural form-finding and geometry morphologies.

Full Content Please See the PDF Documentation

Software Tool & Plugin:

  • Rhino 3D
  • Grasshopper 3D
  • Python
  • Anaconda
  • MOpossum
  • Goat
  • Octopus
  • Galapagos

Algorithm

  • Single-Objective Optimization
  • Multi-Objective Optimization
  • Supervised Learning
  • Unsupervised Learning
  • Deep Learning
  • Generative Deep Learning

Library:

  • Tensorflow
  • Pandas
  • Scikit-learn

[Goal] To Find Most Optimized Shape(s) For Free-Form Concrete Shell Using Novel Strategies

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Single-Objective Optimization [SOO]

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Multi-Objective Optimization [MOO]

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Unsupervised Learning

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Supervised Learning

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Deep Learning

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Generative Deep Learning: Style Transfer for Shell Substructure

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Generative Deep Learning: Brick Facade Patterning

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Explores the application potentials with single-objective optimization, multiple objective optimizations, supervised learning, unsupervised learning and deep learning in architectural fields. This study focuses on developing an optimization workflow for global structural form-finding and geometry morphologies.

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