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Housing

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A machine learning approach to small area estimation: predicting the health, housing and well-being of the population of Netherlands.

International journal of health geographics
BACKGROUND: Local policymakers require information about public health, housing and well-being at small geographical areas. A municipality can for example use this information to organize targeted activities with the aim of improving the well-being o...

Combining deep learning and crowd-sourcing images to predict housing quality in rural China.

Scientific reports
Housing quality is essential to human well-being, security and health. Monitoring the housing quality is crucial for unveiling the socioeconomic development status and providing political proposals. However, depicting the nationwide housing quality i...

Advancing ensemble learning techniques for residential building electricity consumption forecasting: Insight from explainable artificial intelligence.

PloS one
Accurate electricity consumption forecasting in residential buildings has a direct impact on energy efficiency and cost management, making it a critical component of sustainable energy practices. Decision tree-based ensemble learning techniques are p...

Deep Learning Models for Health-Driven Forecasting of Indoor Temperatures in Heat Waves in Canada: An Exploratory Study Using Smart Thermostats.

Studies in health technology and informatics
In Canada, extreme heat occurrences present significant risks to public health, particularly for vulnerable groups like older individuals and those with pre-existing health conditions. Accurately predicting indoor temperatures during these events is ...

Development of a High-Resolution Indoor Radon Map Using a New Machine Learning-Based Probabilistic Model and German Radon Survey Data.

Environmental health perspectives
BACKGROUND: Radon is a carcinogenic, radioactive gas that can accumulate indoors and is undetected by human senses. Therefore, accurate knowledge of indoor radon concentration is crucial for assessing radon-related health effects or identifying radon...

Forecasting second-hand house prices in China using the GA-PSO-BP neural network model.

PloS one
While the traditional genetic algorithms are capable of forecasting house prices, they often suffer from premature convergence, which adversely affects the reliability of the forecasts. To address this issue, the research employs a genetic-particle s...

Extracting Housing and Food Insecurity Information From Clinical Notes Using cTAKES.

Health services research
OBJECTIVE: To assess the utility and challenges of using natural language processing (NLP) in electronic health records (EHRs) to ascertain health-related social needs (HRSNs) among older adults.

Identifying predictors of spatiotemporal variations in residential radon concentrations across North Carolina using machine learning analytics.

Environmental pollution (Barking, Essex : 1987)
Radon is a naturally occurring radioactive gas derived from the decay of uranium in the Earth's crust. Radon exposure is the leading cause of lung cancer among non-smokers in the US. Radon infiltrates homes through soil and building foundations. This...

Modeling the latent impacts of extreme floods on indoor mold spores in residential buildings: Application of machine learning algorithms.

Environment international
Floods can severely impact the economy, environment and society. These impacts can be direct and indirect. Past research has focused more on the former impacts. Of the indirect impacts, those on mold growth in indoor environments that affect human re...

Real estate valuation with multi-source image fusion and enhanced machine learning pipeline.

PloS one
The automated valuation model (AVM) has been widely used by real estate stakeholders to provide accurate property value estimations automatically. Traditional valuation models are subjective and inaccurate, and previous studies have shown that machin...