Multiscale numerical assessment of urban overheating under climate projections: A review
Climate change and urbanization have exacerbated concerns about urban overheating,
affecting thermal comfort, heat-related mortality, and urban energy consumption, especially …
affecting thermal comfort, heat-related mortality, and urban energy consumption, especially …
What are the implications of climate change for retrofitted historic buildings? A literature review
Historic buildings account for more than one-quarter of Europe's existing building stock and
are going to be crucial in the achievement of future energy targets. Although a drastic …
are going to be crucial in the achievement of future energy targets. Although a drastic …
An alternative approach for measuring the mechanical properties of hybrid concrete through image processing and machine learning
Image processing (IP), artificial neural network (ANN), and adaptive neuro-fuzzy inference
system (ANFIS) are innovative techniques in computer science that have been widely used …
system (ANFIS) are innovative techniques in computer science that have been widely used …
Green building envelope designs in different climate and seismic zones: Multi-objective ANN-based genetic algorithm
In recent years, the major component of green building designs adopted by governments in
order to reduce CO 2 emissions as well as energy consumption is the green building …
order to reduce CO 2 emissions as well as energy consumption is the green building …
Reliability analysis of strength models for short-concrete columns under concentric loading with FRP rebars through Artificial Neural Network
Over the last decade, the utilization of fiber-reinforced polymers (FRP) has been increased
due to their versatile properties in concrete columns as a replacement of steel bars and their …
due to their versatile properties in concrete columns as a replacement of steel bars and their …
Predicting Energy Consumption Using Stacked LSTM Snapshot Ensemble
MA Alghamdi, S Abdullah… - Big Data Mining and …, 2024 - ieeexplore.ieee.org
The ability to make accurate energy predictions while considering all related energy factors
allows production plants, regulatory bodies, and governments to meet energy demand and …
allows production plants, regulatory bodies, and governments to meet energy demand and …
Prediction of columns with GFRP bars through Artificial Neural Network and ABAQUS
The objective of this study is to compare the conventional models used for estimating the
ultimate response of Concrete Columns with Glass Fiber Reinforced Polymers (GFRPs) bars …
ultimate response of Concrete Columns with Glass Fiber Reinforced Polymers (GFRPs) bars …
Forecasting Time‐Series Energy Data in Buildings Using an Additive Artificial Intelligence Model for Improving Energy Efficiency
Building energy efficiency is important because buildings consume a significant energy
amount. The study proposed additive artificial neural networks (AANNs) for predicting …
amount. The study proposed additive artificial neural networks (AANNs) for predicting …
A review on behavioural propensity for building load and energy profile development–Model inadequacy and improved approach
To achieve building energy conservation goals, models for forecasting energy consumption
with energy-related occupant behavior inclusive must be encompassed in energy …
with energy-related occupant behavior inclusive must be encompassed in energy …
Simulation of Quantity and Quality of Saq Aquifer Using Artificial Intelligence and Hydraulic Models
Scarcity of water resources is becoming a threatening issue in arid regions like Gulf.
Accurate prediction of quantities and quality of groundwater is the first step towards better …
Accurate prediction of quantities and quality of groundwater is the first step towards better …