AI Medical Compendium Journal:
Chemosphere

Showing 81 to 90 of 147 articles

Air quality index forecast in Beijing based on CNN-LSTM multi-model.

Chemosphere
Accurate predicting the air quality trend can provide a theoretical basis for environmental protection management and decision-making. This study proposed the convolutional neural networks-long short-term memory (CNN-LSTM) model, which was proposed t...

Extraction of multi-scale features enhances the deep learning-based daily PM forecasting in cities.

Chemosphere
Characterising the daily PM2.5 concentration is crucial for air quality control. To govern the status of the atmospheric environment, a novel hybrid model for PM2.5 forecasting was proposed by introducing a two-stage decomposition technology of compl...

Deep learning hybrid predictions for the amount of municipal solid waste: A case study in Shanghai.

Chemosphere
It is crucial to precisely estimate the municipal solid waste (MSW) amount for its sustainable management. Owing to learning complicated and abstract features between the factors and target, deep learning has recently emerged as one of the useful too...

Recycling waste classification using emperor penguin optimizer with deep learning model for bioenergy production.

Chemosphere
The growth and implementation of biofuels and bioenergy conversion technologies play an important part in the production of sustainable and renewable energy resources in the upcoming years. Recycling sources from waste could efficiently ease the risk...

Exploring the potential of in silico machine learning tools for the prediction of acute Daphnia magna nanotoxicity.

Chemosphere
Engineered nanomaterials (ENMs) are ubiquitous nowadays, finding their application in different fields of technology and various consumer products. Virtually any chemical can be manipulated at the nano-scale to display unique characteristics which ma...

Machine learning-assisted non-target analysis of a highly complex mixture of possible toxic unsymmetrical dimethylhydrazine transformation products with chromatography-mass spectrometry.

Chemosphere
Unsymmetrical dimethylhydrazine (UDMH) is a toxic and environmentally hostile compound that was massively introduced to the environment during previous decades due to its use in the space and rocket industry. The compound forms multiple transformatio...

Mapping of groundwater productivity potential with machine learning algorithms: A case study in the provincial capital of Baluchistan, Pakistan.

Chemosphere
Although groundwater (GW) potential zoning can be beneficial for water management, it is currently lacking in several places around the world, including Pakistan's Quetta Valley. Due to ever increasing population growth and industrial development, GW...

Modeling of Remora Optimization with Deep Learning Enabled Heavy Metal Sorption Efficiency Prediction onto Biochar.

Chemosphere
Environmental distresses linked to heavy metal (HM) impurity in the water received significant attention among research communities. Recently, advancements in industrial sectors like paper industries, mining, non-ferrous metallurgy, electroplating, m...

Arithmetic optimization algorithm with deep learning enabled airborne particle-bound metals size prediction model.

Chemosphere
Recently, heavy metal air pollution has received significant interest in computing the total concentration of every toxic metal. Chemical fractionation of possibly toxic substances in airborne particles becomes a vital element. Among the primary and ...

Rapid detection of ionic contents in water through sensor fusion and convolutional neural network.

Chemosphere
Salt contents in soil or groundwater are one of the primary indicators to evaluate contamination levels. Electrical conductivity (EC) or salinity information from the conventional laboratory analysis is typically inefficient in delineating contaminat...