Developing an Alternative Calculation Method for the Smart Readiness Indicator Based on Genetic Programming and Linear Regression

The European Union is planning to introduce a new tool for evaluating smart solutions in buildings—the Smart Readiness Indicator (SRI). As 54 energy efficiency categories must be evaluated, the triage process can be long and time-intensive. Altogether, 228 data points (or inputs) about the smartness of the buildings are required to complete the evaluation. The present paper proposes an alternative calculation method based on genetic programming (GP) for the calculation of Domains and linear regression (LR) for the calculation of Impact Factors and the total SRI score of the building. This novel calculation requires 20% (Domain ventilation and dynamic building envelope) to 75% (Domain cooling) fewer inputs than the original methodology. The present study evaluated 223 case study buildings, and 7 genetic programming models and 8 linear regression models were generated based on the results. The generated results are precise; the relative deviation from the experimental data for Domain scores (modelled with GP) ranged from 0.9% to 2.9%. The R2 for the LR models was 0.75 for most models (with two exceptions, with one with a value of 0.57 and the other with a value of 0.98). The developed method is scalable and could be used for preliminary and portfolio-level screening at early-stage assessments.

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Publication Details

Journal
Buildings
Published
2025-05-15
DOI
https://doi.org/10.3390/buildings15101675
Citations
1
Primary Topic
Technology Assessment and Management
Type
article
Field-Weighted Citation Impact
1.30
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article

Developing an Alternative Calculation Method for the Smart Readiness Indicator Based on Genetic Programming and Linear Regression

Uroš Župerl, M. Brezočnik, Miha Kovačić, Mitja Beras
1 citations
Buildings
Technology Assessment and Management
1.30
article

Developing an Alternative Calculation Method for the Smart Readiness Indicator Based on Genetic Programming and Linear Regression

Uroš Župerl, M. Brezočnik, Miha Kovačić, Mitja Beras
article en
1 citations

Abstract

The European Union is planning to introduce a new tool for evaluating smart solutions in buildings—the Smart Readiness Indicator (SRI). As 54 energy efficiency categories must be evaluated, the triage process can be long and time-intensive. Altogether, 228 data points (or inputs) about the smartness of the buildings are required to complete the evaluation. The present paper proposes an alternative calculation method based on genetic programming (GP) for the calculation of Domains and linear regression (LR) for the calculation of Impact Factors and the total SRI score of the building. This novel calculation requires 20% (Domain ventilation and dynamic building envelope) to 75% (Domain cooling) fewer inputs than the original methodology. The present study evaluated 223 case study buildings, and 7 genetic programming models and 8 linear regression models were generated based on the results. The generated results are precise; the relative deviation from the experimental data for Domain scores (modelled with GP) ranged from 0.9% to 2.9%. The R2 for the LR models was 0.75 for most models (with two exceptions, with one with a value of 0.57 and the other with a value of 0.98). The developed method is scalable and could be used for preliminary and portfolio-level screening at early-stage assessments.

BuildingsVol. 15(10)
University of Ljubljana (SI), University of Maribor (SI), Štore Steel (Slovenia) (SI), College of Industrial Engineering (SI)
Openalex Percentile: Top 21%
Technology Assessment and Management
1.30
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