- News
All the latest updates on building safety reformRegulations latest
- Focus
- Comment
- Programmes
- CPD
- Building the Future
- Jobs
- Data
- Subscribe
- Events
2024 events calendar
Explore nowBuilding Awards
Keep up to date
- Building Boardroom
All the latest updates on building safety reform
2024 events calendar
Explore nowBuilding Awards
Keep up to dateBy Tristan Harvey-Rice and Edward Day 2019-10-01T05:00:00
The use of machine learning could improve the way we predict cost, quantity, schedule and outcomes for the built environment
Machine learning covers a range of techniques that allow computers to improve at a specific task without bespoke programming, in an automated fashion.
Machine learning’s deep analysis allows us to deal more effectively with imperfect data, find patterns within a dataset and produce models from those patterns. We can then use these models to make predictions based on the historic patterns identified.
The application of machine learning has previously largely been restricted to highly complex problems where the associated investment can be justified – rarely in the built environment. But recent advances in processing power, storage capacity and cloud services have brought the computing capability and statistical expertise into the affordable reach of commercial organisations, and in much shorter timescales than before.
Read more…
Existing subscriber? LOGIN
Stay at the forefront of thought leadership with news and analysis from award-winning journalists. Enjoy company features, CEO interviews, architectural reviews, technical project know-how and the latest innovations.
Get your free guest access SIGN UP TODAY
Subscribe to Building today and you will benefit from:
View our subscription options and join our community