AI Medical Compendium Journal:
Environmental research

Showing 71 to 80 of 109 articles

Application of machine learning and deep learning methods for hydrated electron rate constant prediction.

Environmental research
Accurately determining the second-order rate constant with e (k) for organic compounds (OCs) is crucial in the e induced advanced reduction processes (ARPs). In this study, we collected 867 k values at different pHs from peer-reviewed publications an...

A novel deep learning ensemble model based on two-stage feature selection and intelligent optimization for water quality prediction.

Environmental research
Accurate prediction of effluent total nitrogen (E-TN) can assist in feed-forward control of wastewater treatment plants (WWTPs) to ensure effluent compliance with standards while reducing energy consumption. However, multivariate time series predicti...

An artificial neural network-based data filling approach for smart operation of digital wastewater treatment plants.

Environmental research
With the prevalence of digitization, smart operation has become mainstream in future wastewater treatment plants. This requires substantial and complete historical data for model construction. However, the data collected from the front-end sensor con...

Deep convolutional neural network with sine cosine algorithm based wastewater treatment systems.

Environmental research
Wastewater treatment systems are essential in today's business to meet the ever-increasing requirements of environmental regulations while also limiting the environmental impact of the sector's discharges. A new control and management information sys...

Predicting ammonia nitrogen in surface water by a new attention-based deep learning hybrid model.

Environmental research
Ammonia nitrogen (NH-N) is closely related to the occurrence of cyanobacterial blooms and destruction of surface water ecosystems, and thus it is of great significance to develop predictive models for NH-N. However, traditional models cannot fully co...

A multi-scale evolutionary deep learning model based on CEEMDAN, improved whale optimization algorithm, regularized extreme learning machine and LSTM for AQI prediction.

Environmental research
With the rapid development of economy, air pollution occurs frequently, which has a huge negative impact on human health and urban ecosystem. Air quality index (AQI) can directly reflect the degree of air pollution. Accurate AQI trend prediction can ...

Root-zone soil moisture estimation based on remote sensing data and deep learning.

Environmental research
Soil moisture in the root zone is the most important factor in eco-hydrological processes. Even though soil moisture can be obtained by remote sensing, limited to the top few centimeters (<5 cm). Researchers have attempted to estimate root-zone soil ...

Online learning-empowered smart management for AO process in sewage treatment processes.

Environmental research
Using artificial intelligence method to describe general working process is a more meaningful and widely used idea in various practical projects. At the same time, it is also an important way to realize intelligent management. Water pollution is seri...

Water quality prediction model using Gaussian process regression based on deep learning for carbon neutrality in papermaking wastewater treatment system.

Environmental research
Wastewater recycling is the measure with enormous potentiality to achieve carbon neutrality in wastewater treatment plants. High-precision online monitoring can improve the stability of wastewater treatment system and help wastewater recycling. A new...

Identification of environmental microorganism using optimally fine-tuned convolutional neural network.

Environmental research
To not only optimize the hyper-parameters of the classification layer of dense convolutional network with 201 convolutional layers (DenseNet-201) but also use data augmentation processes could enhance the performance of DenseNet-201, and DenseNet-201...