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Machine learning presents opportunities for tracking evidence on climate change adaptation, including text-based methods from natural language processing. In theory, such tools can analyse more data in less time, using fewer resources and with less risk of bias. However, the first generation of adaptation studies have delivered only proof of concepts. Reviewing these first studies, we argue that future efforts should focus on creating more diverse datasets, investigating concrete hypotheses,...

The aim of this study is to present a novel data-driven approach developed for space heating energy demand calculation of the whole EU building stock. To develop a computationally efficient bottom-up model that takes into account building physics parameters and details of the building stock make-up, an artificial neural network (ANN) is trained on a dataset of precise building-physics models. For this purpose, 2025 building energy simulations were performed in this study, ensuring...

With increasing energy consumption, how to achieve the energy-saving operation of air-conditioning systems is crucial for improving the energy efficiency of buildings. The accurate and reliable energy consumption prediction of air-conditioning systems can be useful for optimizing the energy supply and equipment operation strategies. However, most existing studies focus on the prediction of the long-term energy consumption of air-conditioning systems, which usually exceeds the individual...

Deep learning models have been increasingly applied in the field of solar radiation prediction. However, the characteristics of a deep learning black box model restrict its application in practical scenarios such as model predictive control. Because energy system controllers may be unable to make final decisions based solely on the predictions of a black-box model. This study considers both the temporal and spatial dependencies of solar radiation predictions through unfolding sequences and...

Individuals globally spend about 88–92% of their entire time in the indoor environment. The implementation of regularly scheduled systems operation is common in many commercial and residential building types. Occupant Behavior (OB) is highly stochastic, making it difficult to depict the human factor using simple schedules. In the present work, window-opening tendencies were found to be highest in summer and transition seasons and lowest during winter. The Air Changes per Hour (ACH) value...

The climate system is an excellent example of a “complex system” since there is an interplay and inter-relation of several climate variables. Variables such as the Standardized Precipitation Index (SPI) are used to indicate the drought climate condition – a negative (or positive) value of SPI would imply a dry (or wet) state in a region. It is difficult to identify the factors influencing the SPI or their inter-relations (including feedback loops). Here, we aim to study the complex dynamics...

The climate system is an excellent example of a “complex system” since there is an interplay and inter-relation of several climate variables. Variables such as the Standardized Precipitation Index (SPI) are used to indicate the drought climate condition – a negative (or positive) value of SPI would imply a dry (or wet) state in a region. It is difficult to identify the factors influencing the SPI or their inter-relations (including feedback loops). Here, we aim to study the complex dynamics...

Solar shading devices, such as Venetian blinds, are effective in controlling heat and light gain in buildings. This study focuses on developing an Artificial Neural Network (ANN) to automate the management of Venetian blinds in order to find a balance between energy savings and visual comfort. Typically, automatic control strategies rely on cut-off angles or maintaining appropriate indoor illuminance. However, finding the optimal trade-off between solar gain and daylight is challenging,...

In response to climate change, urban blue-green infrastructure (UBGI) improves the microclimate of the built environment. In previous research, UBGI (consisting of water and greenery) is found to be a cold source in the summer, alleviating urban thermal stress. However, studies on the heating effect of UBGI in the winter are limited. This effect can improve environmental temperature, which is beneficial to human thermal comfort in the cold season. Therefore, this study conducted the...

In response to climate change, urban blue-green infrastructure (UBGI) improves the microclimate of the built environment. In previous research, UBGI (consisting of water and greenery) is found to be a cold source in the summer, alleviating urban thermal stress. However, studies on the heating effect of UBGI in the winter are limited. This effect can improve environmental temperature, which is beneficial to human thermal comfort in the cold season. Therefore, this study conducted the...

Model-based optimal control has proven its effectiveness in optimizing the performance of central air-conditioning systems in terms of thermal comfort and energy efficiency. It was often assumed that temperature distribution in the entire air-conditioned space is uniform and can be represented by a single or averaged measurement in optimization. However, actual distribution in the air-conditioned space is usually uneven, which can affect thermal comfort and indoor air quality. The dynamics...

In an increasingly digital world, there are fast-paced developments in fields such as Artificial Intelligence, Machine Learning, Data Mining, Digital Twins, Cyber-Physical Systems and the Internet of Things. This paper reviews and discusses how these new emerging areas relate to the traditional domain of building performance simulation. It explores the boundaries between building simulation and these other fields in order to identify conceptual differences and similarities, strengths and...

Energy studies of buildings are becoming more widespread as stakeholders strive to improve energy efficiency and reduce carbon emissions. As a result, there is an increased need for novel numerical techniques to automatically calibrate building energy models (BEMs) for these energy studies. In this paper, a new automated building calibration methodology was developed, which uses a surrogate (i.e., meta) multilayer perceptron artificial neural network (ANN) to infer unknown building...

This paper investigates the use of dilated causal convolutional neural networks for fine-grained temporal forecasting of building zone states. Specifically, we build and evaluate models using a small set of exogenous features (e.g., external temperature) to autoregressively predict zone airflow setpoints every minute for a 24-h prediction window. We carefully explore the trade-off between generality and specificity in these models, training and evaluating them based on zone, zone type,...

The revolution of the industry 4.0 presents a new era of digital transformation for the construction industry, advancing towards the concept of digital twins, while on the other hand it faces the global challenge of reducing carbon emissions from operational assets. The current research gap in the application of digital twins for achieving net zero were reviewed in this study, highlighting its potentials for enhancement in the built environment, and emphasizing the need for demonstration of...

Environmental degradation and carbon emissions have become a major global concern. This has forced policymakers to consider strategic and long-term contingencies to increase carbon sequestration capacity and mitigate the effects of climate change. Soil organic carbon (SOC) provides a reliable long-lasting mechanism to ameliorate climate change and regulate carbon fluxes. However, unanticipated rates of climate change coupled with the dynamic nature of land-use transformation threatens...

Environmental degradation and carbon emissions have become a major global concern. This has forced policymakers to consider strategic and long-term contingencies to increase carbon sequestration capacity and mitigate the effects of climate change. Soil organic carbon (SOC) provides a reliable long-lasting mechanism to ameliorate climate change and regulate carbon fluxes. However, unanticipated rates of climate change coupled with the dynamic nature of land-use transformation threatens...

The Standardized Precipitation Index (SPI) is used to indicate the meteorological drought situation - a negative (or positive) value of SPI would imply a dry (or wet) condition in a region over a period. The climate system is an excellent example of a complex system since there is an interplay and inter-relation of several climate variables. It is not always easy to identify the factors that may influence the SPI, or their inter-relations (including feedback loops). Here, we aim to study the...

The Standardized Precipitation Index (SPI) is used to indicate the meteorological drought situation - a negative (or positive) value of SPI would imply a dry (or wet) condition in a region over a period. The climate system is an excellent example of a complex system since there is an interplay and inter-relation of several climate variables. It is not always easy to identify the factors that may influence the SPI, or their inter-relations (including feedback loops). Here, we aim to study the...

Recently, Occupant-Centric Control (OCC) strategies have gained mounting interest. Previous studies made use of OCC strategies for adjusting the operation of heating/cooling systems, improving indoor thermal comfort and governing mechanical ventilation systems. However, a very limited number of studies have applied OCC strategies to natural ventilation systems. Further, the feasibility of establishing OCC strategies for controlling indoor thermal comfort, energy use and specifically air...