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£100.11
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Springer - Data-Driven Modelling of Building Energy Performance
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Description
Key Features
This Springer publication outlines data-driven modelling techniques specifically for non-domestic building energy performance.
The text provides guidance on determining the appropriate machine learning model for various retrofit planning applications.
Learn methods for the selection and expansion of reasonable datasets to improve energy performance analysis.
The book explains how to extract relevant features and maximize model accuracy for better decision-making.
A framework is developed for the quick selection of machine learning models based on specific data and applications.
Includes a method for optimizing machine learning models for forecasting building energy loads using evolutionary algorithms.
Product Specifications
- Brand
- Springer
- Format
- paperback
- ASIN
- 3030647536
- Category
- Books > Subjects > Arts & Photography > Architecture > Design > Sustainability & Green Design
- Domain
- Amazon UK
- Release Date
- 16 January 2022
- Listed Since
- 21 December 2021
Barcode
No barcode data available
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