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Temperature

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The assessment of response surface methodology (RSM) and artificial neural network (ANN) modeling in dry flue gas desulfurization at low temperatures.

Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering
The performance of a flue gas desulfurization (FGD) system is characterized by SO removal efficiency () and reagent conversion (). Achieving a near-perfect reaction environment has been of concern in dry FGD (DFGD) due to the low reactivity compared ...

Prediction of cooling effect of constant temperature community bin based on BP neural network.

International journal of biometeorology
In order to explore the influence of outdoor microclimate on the cooling effect of constant temperature community bin, the temperature prediction model was predicted. The temperature and microclimate data sets of the community bin were collected in s...

Prediction of human thermal comfort preference based on supervised learning.

Journal of thermal biology
Human thermal comfort is relevant to human life comfort and plays a pivotal role in occupational health and thermal safety. To ensure that intelligent temperature-controlled equipment can deliver a sense of cosiness to people while improving its ener...

Explainable deep learning for insights in El Niño and river flows.

Nature communications
The El Niño Southern Oscillation (ENSO) is a semi-periodic fluctuation in sea surface temperature (SST) over the tropical central and eastern Pacific Ocean that influences interannual variability in regional hydrology across the world through long-ra...

Uncertainty and sensitivity analysis of deep learning models for diurnal temperature range (DTR) forecasting over five Indian cities.

Environmental monitoring and assessment
In this article, the maximum and minimum daily temperature data for Indian cities were tested, together with the predicted diurnal temperature range (DTR) for monthly time horizons. RClimDex, a user interface for extreme computing indices, was used t...

Hybrid Feature Fusion-Based High-Sensitivity Fire Detection and Early Warning for Intelligent Building Systems.

Sensors (Basel, Switzerland)
High-sensitivity early fire detection is an essential prerequisite to intelligent building safety. However, due to the small changes and erratic fluctuations in environmental parameters in the initial combustion phase, it is always a challenging task...

The Development of an Energy Efficient Temperature Controller for Residential Use and Its Generalization Based on LSTM.

Sensors (Basel, Switzerland)
Thermostats operate alongside intelligent home automation systems for ensuring both the comfort of the occupants as well as the responsible use of energy. The effectiveness of such solutions relies on the ability of the adopted control methodology to...

A soft sensing method of billet surface temperature based on ILGSSA-LSSVM.

Scientific reports
It is difficult to measure the surface temperature of continuous casting billet, which results in the lack of important feedback parameters for further scientific control of the billet quality. This paper proposes a sparrow search algorithm to optimi...

Urban Heat Island Intensity Changes in Guangdong-Hong Kong-Macao Greater Bay Area of China Revealed by Downscaling MODIS LST with Deep Learning.

International journal of environmental research and public health
The urban heat island (UHI) effect caused by urbanization negatively impacts the ecological environment and human health. It is crucial for urban planning and social development to monitor the urban heat island effect and study its mechanism. Due to ...

Machine learning and statistical analysis for biomass torrefaction: A review.

Bioresource technology
Torrefaction is a remarkable technology in biomass-to-energy. However, biomass has several disadvantages, including hydrophilic properties, higher moisture, lower heating value, and heterogeneous properties. Many conventional approaches, such as kine...