Innovative methodologies for the design of Zero-Emission and cost-effective Buildings enhanced by Artificial Intelligence

Informations projet

ZEBAI

N° de convention de subvention: 101138678

DOI

10.3030/101138678

Date de signature de la CE 14 Decembre 2023

Date de début 1 Janvier 2024

Date de fin 31 Decembre 2028

Financé au titre de

• Climate, Energy and Mobility

Coût total

€ 4 355 763,85

Contribution de l’UE

€ 3 879 168,25

Coordonné par

UNIVERSIDAD POLITECNICA DE MADRID
Spain

CORDIS fournit des liens vers les livrables publics et les publications des projets HORIZON.

Les liens vers les livrables et les publications des projets du 7e PC, ainsi que les liens vers certains types de résultats spécifiques tels que les jeux de données et les logiciels, sont récupérés dynamiquement sur OpenAIRE .

Livrables

Documents, reports (4)

Report on existing European material catalogues for construction

This report will compile the different catalogues that contain information on performance, sustainability aspects and/or cost of mature construction materials selected from a complete survey at a European level. An analysis of the structure of the catalogues, their access requirements and the commonalities and differences between them will be included.

Report on the methods and models for the simulation error minimisation

We will review and analyse the existing methods and models for the simulation error minimization and corresponding tools for it. We will prepare a report based on the results obtained. This will help determine the direction of execution (D5.5)

Methodology Design Handbook [MDH]

In this document, the best strategy to ambitiously tackle the ZEB optimization problem will be formulated in order to guarantee the quality and robustness of the IA proposed solutions. A detailed description on inputs/outputs, constraints, quality functions and freedom degree of the solution space will be presented.

ZEBAI Methodology Handbook [ZMH]

The methodology handbook proposes new design methodologies and related design processes that have been used for the design of zero-emission and cost-effective buildings.

Data Management Plan (1)

Data Management Plan [DMP]

This document describes the DM life cycle for the data to be collected, stored, processed, shared, and/or generated. It includes information on the data's format, collection methodology, storage, backup, sharing and access, analysis and processing, ethics and legal considerations, and roles and responsibilities of the individuals involved. This deliverable will be in effect throughout the project. An initial release will be provided in month 6, but updates will be delivered in month 30 and 60.

Data sets, microdata, etc (1)

Retrospective cases dataset (BIM building models and sensor datasets)

We will collect a dataset of retrospective cases of monitored buildings already existing and their corresponding digital models for simulation.

Publications

Peer reviewed articles (11)

Scientific Reports

Auteurs: Ivan Izonin; Illia Nesterenko; Athanasia K. Kazantzi; Roman Tkachenko; Roman Muzyka; Stergios Aristoteles Mitoulis
Publié dans: Scientific Reports, Numéro 14, 2024, ISSN 2045-2322
Éditeur: Nature Publishing Group
DOI: 10.1038/S41598-024-73738-5

Regression-based Model for Predicting Simulated vs Actual Building Performance Discrepancies

Auteurs: Ivan Izonin, Roman Tkachenko, Rosana Caro, Antonio LaTorre de la Fuente, Kyrylo Yemets, Stergios Aristoteles Mitoulis
Publié dans: Procedia Computer Science, Numéro 251, 2025, ISSN 1877-0509
Éditeur: Elsevier BV
DOI: 10.1016/j.procs.2024.11.161

Enhancing the FFT-LSTM Time-Series Forecasting Model via a Novel FFT-Based Feature Extraction–Extension Scheme

Auteurs: Kyrylo Yemets, Ivan Izonin, Ivanna Dronyuk
Publié dans: Big Data and Cognitive Computing, Numéro 9, 2025, ISSN 2504-2289
Éditeur: MDPI AG
DOI: 10.3390/bdcc9020035

Time Series Forecasting Model Based on the Adapted Transformer Neural Network and FFT-Based Features Extraction

Auteurs: Kyrylo Yemets, Ivan Izonin, Ivanna Dronyuk
Publié dans: Sensors, Numéro 25, 2025, ISSN 1424-8220
Éditeur: MDPI AG
DOI: 10.3390/s25030652

Nature-inspired swarm optimization paradigms for securing semantic web frameworks against DDoS attacks: a computational approach

Auteurs: Chirag Ganguli, Shishir Kumar Shandilya, Ivan Izonin, Lesia Hentosh
Publié dans: Scientific Reports, Numéro 15, 2025, ISSN 2045-2322
Éditeur: Springer Science and Business Media LLC
DOI: 10.1038/S41598-025-26058-1

High-Fidelity Synthetic Data Generation Framework for Unique Objects Detection

Auteurs: Shakhovska, Natalya; Sydor, Bohdan; Liaskovska, Solomiya; Duran, Olga; Martyn, Yevgen; Віра, Володимир
Publié dans: computation, Numéro 13, 2025, ISSN 2079-3197
Éditeur: MDPI
DOI: 10.3390/COMPUTATION13050120

Systematic Generation and Evaluation of Synthetic Production Data for Industry 5.0 Optimization

Auteurs: Solomiia Liaskovska, Sviatoslav Tyskyi, Yevgen Martyn, Andy T. Augousti, Volodymyr Kulyk
Publié dans: Technologies, Numéro 13, 2025, ISSN 2227-7080
Éditeur: MDPI AG
DOI: 10.3390/technologies13020084

Advancements in AI-Based Information Technologies: Solutions for Quality and Security

Auteurs: Tetiana Hovorushchenko; Ivan Izonin; Hakan Kutucu
Publié dans: Systems, Numéro 12, 2024, ISSN 2079-8954
Éditeur: MDPI
DOI: 10.3390/SYSTEMS12020058

Multi-family wavelet-based feature engineering method for short-term time series forecasting

Auteurs: Kyrylo Yemets, Ivan Izonin, Stergios Aristoteles Mitoulis
Publié dans: Scientific Reports, Numéro 15, 2025, ISSN 2045-2322
Éditeur: Springer Science and Business Media LLC
DOI: 10.1038/S41598-025-26685-8

Scientific Reports

Auteurs: Ivan Izonin, Illia Nesterenko, Athanasia K. Kazantzi, Roman Tkachenko, Roman Muzyka, Stergios Aristoteles Mitoulis
Publié dans: Scientific Reports, Numéro 14, 2024, ISSN 2045-2322
Éditeur: Nature Publishing Group
DOI: 10.1038/S41598-024-73738-5

Multi-Step Dynamic Ensemble Selection to Estimate Software Effort

Auteurs: Akshay Jadhav; Shishir Kumar Shandilya; Ivan Izonin; Roman Muzyka
Publié dans: Applied Artificial Intelligence, Numéro 38, 2024, ISSN 1087-6545
Éditeur: Taylor & Francis
DOI: 10.1080/08839514.2024.2351718

Other (2)

Quality and Security of Critical Infrastructure Systems

Auteurs: Ivan Izonin, Tetiana Hovorushchenko, Shishir Kumar Shandilya
Publié dans: Big Data and Cognitive Computing, Numéro 8, 2024, ISSN 2504-2289
Éditeur: MDPI
DOI: 10.3390/BDCC8010010

Quality and Security of Critical Infrastructure Systems

Auteurs: Ivan Izonin; Tetiana Hovorushchenko; Shishir Kumar Shandilya
Publié dans: Big Data and Cognitive Computing, Numéro 8, 2024, ISSN 2504-2289
Éditeur: MDPI
DOI: 10.3390/BDCC8010010