- author = "Mitja Beras and Miran Brezocnik and Uros Zuperl and Miha Kovacic",
- title = "Developing an Alternative Calculation Method for the Smart Readiness Indicator Based on Genetic Programming and Linear Regression",
- journal = "Buildings",
- year = "2025",
- volume = "15",
- number = "10",
- pages = "Article no: 1675",
- month = "15 " # may,
- keywords = "genetic algorithms, genetic programming, SRI, modeling, linear regression, energy efficient buildings, smart buildings, optimisation",
- ISSN = "2075-5309",
-
URL = "
https://www.mdpi.com/2075-5309/15/10/1675",
-
URL = "https://www.human-competitive.org/sites/default/files/humies_2025_entry_submission_-_beras_et_al_.txt",
-
URL = "
https://www.human-competitive.org/sites/default/files/buildings-15-01675-v2.pdf",
-
DOI = "
doi:10.3390/buildings15101675",
- size = "36 pages",
- 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 20percent (Domain ventilation and dynamic building envelope) to 75percent (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 (modeled with GP) ranged from 0.9percent to 2.9percent. 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.",
-
notes = "Entered 2025 HUMIES
Also known as \cite{buildings15101675}
Faculty of Mechanical Engineering, University of Maribor, 2000 Maribor, Slovenia",
