AIMC Topic: Hot Temperature

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Heat loss evaluation for heating building envelope based on relevance vector machine.

PloS one
Due to the influence of many factors, there is no reasonable evaluation method for the heat loss evaluation of the envelope, which leads to the deviation of the evaluation results of building energy consumption. By comparing different regression anal...

Flow and heat transfer of Poly Dispersed SiO2 Nanoparticles in Aqueous Glycerol in a Horizontal pipe: Application of ensemble and evolutionary machine learning for model-prediction.

PloS one
Stable nanofluid dispersion with SiO2 particles of 15, 50, and 100 nm is generated in a base liquid composed of water and glycerol in a 7:3 ratio and tested for physical characteristics in the temperature range of 20-100oC. The nanofluid showed excel...

Predicting the tensile properties of heat treated and non-heat treated LPBFed AlSi10Mg alloy using machine learning regression algorithms.

PloS one
In this study, the ability of machine learning algorithms to predict tensile properties of both heat-treated and non-heat treated LPBFed AlSi10Mg alloy is investigated. The data was analyzed using various Machine Learning Regression (MLR) models such...

Deep learning-based spatial optimization of green and cool roof implementation for urban heat mitigation.

Journal of environmental management
Intensifying urban heat extremes require efficient mitigation strategies; therefore, we propose a methodological framework for optimizing the implementation of urban green and cool roofs to reduce heat stress while maximizing their cost-effectiveness...

AI-based forecasting of dynamic behaviors of Ag and ZnO nanoparticles-enhanced milk in an electromagnetic channel with exponential heating: dairy decontamination.

The European physical journal. E, Soft matter
Electromagnetic plates can be used to heat milk and other dairy products rapidly and uniformly. The use of electromagnetic fields enables precise thermal control, which is crucial for safe pasteurization while retaining the nutritional and sensory qu...

Heat Capacity of Ionic Liquids: Toward Interpretable Chemical Structure-Based Machine Learning Approaches.

Journal of chemical information and modeling
This study focuses on predicting the heat capacity of pure liquid-phase ionic liquids (ILs) using machine learning models from various categories, including support vector machines, instance-based learning, ensemble learning, and neural networks, wit...

Developing a seasonal-adjusted machine-learning-based hybrid time‑series model to forecast heatwave warning.

Scientific reports
Heatwaves pose a significant threat to environmental sustainability and public health, particularly in vulnerable regions and rapidly growing cities. They cause water shortages, stress on plants, and an overall drying out of landscapes, reducing plan...

Automatic analysis of high, medium, and low activities of broilers with heat stress operations via image processing and machine learning.

Poultry science
Heat stress is a major welfare problem in the poultry industry, altering broilers' activity levels. Advancements in image processing and machine learning provide opportunities to automatically quantify and analyze broiler activity. This study aimed t...

Biophysical versus machine learning models for predicting rectal and skin temperatures in older adults.

Journal of thermal biology
This study compares the efficacy of machine learning models to traditional biophysical models in predicting rectal (T) and skin (T) temperatures of older adults (≥60 years) during prolonged heat exposure. Five machine learning models were trained on ...

Deep learning combined Monte Carlo simulation reveal the fundamental light propagation in apple puree: Monitoring the quality changes from different cultivar, storage period and heating duration.

Food research international (Ottawa, Ont.)
This work explored the light propagation of purees from a large variability of apple cultivar, storage period and heating duration based on their optical absorption (μ) and reduced scattering (μ') properties at 900-1650 nm, in order to better monitor...