AIMC Topic: Environmental Pollution

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A stacking ensemble classifier-based machine learning model for classifying pollution sources on photovoltaic panels.

Scientific reports
Solar energy is a very efficient alternative for generating clean electric energy. However, pollution on the surface of solar panels reduces solar radiation, increases surface transmittance, and raises the surface temperature. All these factors cause...

PM2.5 concentration prediction using weighted CEEMDAN and improved LSTM neural network.

Environmental science and pollution research international
As the core of pollution prevention and management, accurate PM2.5 concentration prediction is crucial for human survival. However, due to the nonstationarity and nonlinearity of PM2.5 concentration data, the accurate prediction for PM2.5 concentrati...

Exploring Transformer and Graph Convolutional Networks for Human Mobility Modeling.

Sensors (Basel, Switzerland)
The estimation of human mobility patterns is essential for many components of developed societies, including the planning and management of urbanization, pollution, and disease spread. One important type of mobility estimator is the next-place predic...

A Horizon Scan to Support Chemical Pollution-Related Policymaking for Sustainable and Climate-Resilient Economies.

Environmental toxicology and chemistry
While chemicals are vital to modern society through materials, agriculture, textiles, new technology, medicines, and consumer goods, their use is not without risks. Unfortunately, our resources seem inadequate to address the breadth of chemical chall...

Application of artificial intelligence in solar and wind energy resources: a strategy to deal with environmental pollution.

Environmental science and pollution research international
Environmental pollution has become a significant concern of nations. International organizations, local authorities, and social activists try to achieve sustainable development goals (SDGs) to protect the environment. However, this cannot be achieved...

The predictive model for COVID-19 pandemic plastic pollution by using deep learning method.

Scientific reports
Pandemic plastics (e.g., masks, gloves, aprons, and sanitizer bottles) are global consequences of COVID-19 pandemic-infected waste, which has increased significantly throughout the world. These hazardous wastes play an important role in environmental...

Analysis of YOLOv5 and DeepLabv3+ Algorithms for Detecting Illegal Cultivation on Public Land: A Case Study of a Riverside in Korea.

International journal of environmental research and public health
Rivers are generally classified as either national or local rivers. Large-scale national rivers are maintained through systematic maintenance and management, whereas many difficulties can be encountered in the management of small-scale local rivers. ...

Online sequential, outlier robust, and parallel layer perceptron extreme learning machine models for sediment transport in sewer pipes.

Environmental science and pollution research international
Sediment transport is a noteworthy task in the design and operation of sewer pipes. Decreasing sewer pipe hydraulic capacity and transport of pollution are the main consequences of continuous sedimentation. Among different design approaches, the non-...

Air pollution, water pollution, and robots: Is technology the panacea.

Journal of environmental management
The degradation of the ecological environment caused by industrialization presents a major challenge for policymakers as they aim to develop sustainability. Is there a way to balance industrial growth and environmental sustainability? To answer this ...

Deep learning based approach for automated characterization of large marine microplastic particles.

Marine environmental research
The rapidly growing concern of marine microplastic pollution has drawn attentions globally. Microplastic particles are normally subjected to visual characterization prior to more sophisticated chemical analyses. However, the misidentification rate of...