Parametric Analysis, Generative Design and Machine Learning in Architectural Practice (Practical Revolutions) - Softcover

Über die Autorin bzw. den Autor

Dr Victor Okhoya holds a Doctor of Design in Architecture from Carnegie Mellon University with a specialty in Computational Design, and has worked with architectural computational technology for more than twenty years. He has published widely on architectural computation technology and related subjects, has held leadership roles in digital design technology at leading architectural practices, and has trained hundreds of industry professionals on the use of digital design tools.

Marcelo Bernal, PhD, holds a doctoral degree in Architecture from the Georgia Institute of Technology with a specialty in Computational Design, and has more than two decades' experience in research and architectural practice. He has held professorial positions at the Universidad Techica Federico Santa Maria (UTFSM), Chile, and has published widely on architectural design and related subjects.

Von der hinteren Coverseite

Let these cutting-edge tools revolutionize your architectural problem-solving

Recent technological advances, including rapid development of high-performance computing power, have produced computational tools for architects and designers that are swiftly revolutionizing the field. Two of these tools, parametric analysis and generative design, can be used together to model complex problems and test solutions with extraordinary speed and efficiency. The next generation of architects and designers will bring these tools to bear in a transformed professional landscape.

Parametric Analysis and Generative Design in Architectural Practice offers a detailed introduction to these tools and their applications. Balancing theory and practice, it is replete with useful examples and provides algorithms for three different architectural scales: urban design, building design, and interior design. A foundational discussion on machine learning in architectural practice is presented, along with examples of machine learning applications for energy analysis and solar analysis. It is a must-own for architects looking to leverage an unprecedented level of computational power.

The book also includes:

• Detailed guidelines for building performance simulation for energy analysis and daylight analysis
• Algorithms for scales from interiors to buildings to entire cityscapes
• Discussion of how to implement machine learning in order to solve complex problems

Parametric Analysis and Generative Design in Architectural Practice is ideal for professionals and students at every level looking to diversify their architectural toolkit.