Active learning-based machine learning approach for enhancing environmental sustainability in green building energy consumption

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Aug. 27, 2024

Abstract Green building (GB) techniques are essential for reducing energy waste in the construction sector, which accounts almost 40% of global consumption. Despite their importance, challenges such as occupant behavior and management gaps often result GBs consuming up to 2.5 times more than intended. To address this, Building Automation Systems (BAS) play a crucial role enhancing efficiency. This research develops predictive model GB design using machine learning minimize consumption improve indoor sustainability. The dataset is utilized predict cooling heating individually, with data visualization by graphically illustrating features preprocessing through Z-Score normalization splitting. proposed model, based on active utilizing ML regressors Random Forest (RF), Decision Tree (DT), Gradient Boosting (GB), Extreme (XGBoost), CatBoost (CB), Light Machine (LGBM), K-Nearest Neighbor (KNN), Logistic Regressor (LR), shows significant performance improvements. CBR-AL achieves impressive results values 0.9975 (Y1) 0.9883 (Y2), indicating high level accuracy. model’s success improving sustainability has potential ripple effects, including substantial cost savings, reduced carbon footprints, improved operational efficiency green buildings. approach not only enhances environmental but also sets benchmark future advancements modelling management.

Language: Английский

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Impact of pressure on structural, mechanical, optoelectronic and thermoelectric properties of vacancy-ordered double perovskite K2SeCl6

Next Materials, Journal Year: 2025, Volume and Issue: 8, P. 100512 - 100512

Published: Feb. 18, 2025

Language: Английский

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Particleboards based on agricultural and agroforestry wastes glued with vegetal polyurethane adhesive: An efficient and eco-friendly alternative

Industrial Crops and Products, Journal Year: 2024, Volume and Issue: 214, P. 118540 - 118540

Published: April 13, 2024

Language: Английский

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Integrating machine and deep learning technologies in green buildings for enhanced energy efficiency and environmental sustainability

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Sept. 2, 2024

A green building (GB) is a design idea that integrates environmentally conscious technology and sustainable procedures throughout the building's life cycle. However, because different requirements performances are integrated into design, GB procedure typically takes longer than conventional structures. Machine learning (ML) other advanced artificial intelligence (AI), such as DL techniques, frequently utilized to assist designers in completing their work more quickly precisely. Therefore, this study aims develop predictive model utilizing ML techniques optimize resource consumption, improve occupant comfort, lessen environmental effect of built environment process. dataset ASHARE-884 applied suggested models. An Exploratory Data Analysis (EDA) applied, which involves cleaning, sorting, converting category data numerical values label encoding. In preprocessing, Z-Score normalization technique normalize data. After analysis preprocessed used input for RF, DT, Extreme GB, Stacking Deep Learning (DL) GNN, LSTM, RNN enhance sustainability by addressing criteria The performance proposed models assessed using evaluation metrics accuracy, precision, recall F1-score. experiment results indicate GNN LSTM function accurately efficiently buildings.

Language: Английский

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Adapting Green Building Practices and Smart Technology in Developing Countries

Deleted Journal, Journal Year: 2024, Volume and Issue: 16(1), P. 183 - 202

Published: Oct. 2, 2024

This paper reviews the integration of green building practices and smart technologies in developing countries, focusing on challenges opportunities these regions face. While developed nations have advanced significantly sustainability through certifications systems, countries encounter barriers such as financial constraints, limited technical expertise, insufficient policy frameworks. research employs a systematic literature review to examine case studies from Africa, Southeast Asia, Latin America, exploring how can adapt sustainable their unique socio-economic environmental conditions. The findings reveal that despite significant challenges, offer long-term benefits, including improved energy efficiency, reduced operational costs, enhanced quality life. Successful adaptations, using locally sourced materials implementing low-cost demonstrate feasibility development even with resources. Case Nigeria, South Kenya showcase promising examples where construction has been successfully integrated. contributes existing body knowledge by providing an in-depth analysis factors enabling or hindering adoption nations. concludes stronger governmental support, training, broader awareness campaigns are essential overcoming barriers. Key recommendations include incentives for developers, scaling successful projects, fostering public-private partnerships promote innovation. Additionally, study calls reforms align international goals while considering local challenges. In conclusion, presents viable solution urbanization offering path toward economic resilience.

Language: Английский

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STUDI LITERATUR HAMBATAN SOSIAL DAN BUDAYA PADA PENERAPAN BANGUNAN HIJAU

Jurnal Kacapuri Jurnal Keilmuan Teknik Sipil, Journal Year: 2024, Volume and Issue: 7(2), P. 244 - 244

Published: Dec. 27, 2024

Penelitian ini menggali hambatan sosial dan budaya yang menghalangi adopsi konsep bangunan hijau dalam industri konstruksi serta merancang strategi untuk mengatasi tantangan tersebut. Bangunan hijau, diakui sebagai vital mengurangi emisi karbon meningkatkan efisiensi energi. Namun, faktor-faktor seperti persepsi menentang, kurangnya pemahaman masyarakat, minimnya edukasi formal, pola hidup kurang peduli lingkungan, dukungan pemerintah tidak memadai, semuanya menjadi penghalang signifikan. Studi menggunakan metode studi literatur dengan aplikasi perangkat lunak Publish or Perish mencari mengevaluasi referensi relevan dari tahun 2018 hingga 2024. Hasilnya mengidentifikasi 25 faktor utama terbagi kelompok Budaya Kebiasaan, Kesadaran Pemahaman, Sosialisasi Edukasi, Pola Hidup Kurang Peduli Lingkungan, Dukungan Komitmen Pemerintah. Hasil penelitian menyoroti kompleksitas menawarkan solusi potensial berupa kampanye lebih efektif, peningkatan pelatihan profesional, perbaikan kebijakan pemerintah. diharapkan memberikan wawasan berguna bagi pembuat kebijakan, desainer, pemangku kepentingan mengembangkan dapat diterima secara mempromosikan hijau. Dengan mengintegrasikan elemen ke arsitektur vernakular mempertimbangkan konteks spesifik, masyarakat menerima menerapkan praktik pembangunan berkelanjutan luas.

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