Enhancing the PM2.5 Predictions of US Embassies Using Novel Hybrid 1DCNN-BiGRU and Decomposed-Recomposed 1DCNN-BiGRU-DR Models

Today, no one is untouchable from climate change and its impact on our environmental life and the layers of the atmosphere. Almost every developed and developing country is facing the issue of climate change. Climate change and its effect on the earth’s environment are not new issues.

Naushad Ahmad

Jan 19, 2026

Theoretical and Applied Climatology

Behind the Paper

Effective air pollution prediction using wavenet deep learning with Xgboost (1DCNN-BiLSTM-XgRC) for urban US embassies

The key contributors to climate change include air pollution and atmospheric radiation. Particulate Matter (PM) is especially harmful among various pollutants, posing significant risks to human health and the environment.

Naushad Ahmad

Jan 12, 2026

SN Computer Science

Behind the Paper

Enhancing PM2.5 Air Pollution Forecasting with Novel Random Imputation Based on Hybrid RNN-Bidirectional GRU (nRI RNN-BiGRU) Model

The issue of air pollution is critical for both environment and global public health. It is crucial to develop accurate forecasting method to substantially mitigate the adverse health effects of air pollution. Missing data is common in dataset where specific observations or values are not recorded.

Naushad Ahmad

Jan 08, 2026

Water, Air, & Soil Pollution

Behind the Paper

Spatio-Temporal Forecasting using a Hybrid BiGRU-1DCNN Model for PM2.5 Concentrations in Delhi, India (2018-2023) Across Multiple Monitoring Stations

Air quality deterioration, particularly the suspension of particulate matter over large urban areas, has emerged as a significant environmental concern. This issue, exacerbated by urbanization, industrialization, human activities, and climate change, poses serious health risks to populations.

Naushad Ahmad

Jan 08, 2026

Quantum Machine Intelligence

Behind the Paper

Quantum-inspired neural networks for time-series air pollution prediction and control of the most polluted region in the world

Researchers in the field of quantum computing are primarily focused on quantum-inspired algorithms, which function effectively on classical computers while incorporating quantum principles. A significant challenge in heavily polluted areas is accurately predicting air pollution levels.

Naushad Ahmad

Jan 08, 2026

Naushad Ahmad (He/Him)

Enhancing the PM2.5 Predictions of US Embassies Using Novel Hybrid 1DCNN-BiGRU and Decomposed-Recomposed 1DCNN-BiGRU-DR Models

Effective air pollution prediction using wavenet deep learning with Xgboost (1DCNN-BiLSTM-XgRC) for urban US embassies

Enhancing PM2.5 Air Pollution Forecasting with Novel Random Imputation Based on Hybrid RNN-Bidirectional GRU (nRI RNN-BiGRU) Model

Spatio-Temporal Forecasting using a Hybrid BiGRU-1DCNN Model for PM2.5 Concentrations in Delhi, India (2018-2023) Across Multiple Monitoring Stations

Quantum-inspired neural networks for time-series air pollution prediction and control of the most polluted region in the world

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