[PDF][PDF] Forecast air pollution in smart city using deep learning techniques: a review

GI Drewil, RJ Al-Bahadili - Multicult. Educ, 2021 - ijdri.com
The number of people moving to cities as reported by the Urban Population website for the
year 2019 was 55.714%[‎ 1]. As the UN revealed, it is expected that 68% of the world's …

[HTML][HTML] A systematic review of machine learning approaches in carbon capture applications

F Hussin, SANM Rahim, NSM Hatta, MK Aroua… - Journal of CO2 …, 2023 - Elsevier
Climate change and global warming are among of the most important environmental issues
and require adequate and immediate global action to preserve the planet for future …

Comparative ANFIS Models for Stochastic On-road Vehicle CO2 Emission using Grid Partitioning, Subtractive, and Fuzzy C-means Clustering

MGB Palconit, RS Conception II… - 2021 IEEE 9th …, 2021 - ieeexplore.ieee.org
On-road vehicle CO 2 emission is stochastic and is presently not feasible to be solved using
hard computing methodologies due to computational cost. This paper presents an on-road …

Forecasting of carbon dioxide emissions from power plants in Kuwait using United States Environmental Protection Agency, Intergovernmental panel on climate …

S AlKheder, A Almusalam - Renewable Energy, 2022 - Elsevier
The second largest share of Greenhouse Gas (GHG) emissions is generated by electricity
production. Approximately 63% of the generated electricity is from burning fossil fuels …

Predictability of vehicle fuel consumption using LSTM: Findings from field experiments

G Wang, L Zhang, Z Xu, R Wang, SM Hina… - … Engineering, Part A …, 2023 - ascelibrary.org
It has been well-recognized that driving behaviors significantly impact the fuel consumption
of vehicles. To explore how well deep learning methods can predict fuel consumption …

Road car accident prediction using a machine-learning-enabled data analysis

S Pourroostaei Ardakani, X Liang, KT Mengistu, RS So… - Sustainability, 2023 - mdpi.com
Traffic accidents have become severe risks as they are one of the causes of enormous
deaths worldwide. Reducing the number of incidents is critical to saving lives and achieving …

Application of Artificial Neural Network for Predicting Agricultural Methane and CO2 Emissions in Bangladesh

S Chowdhury, MA Rubi… - 2021 12th international …, 2021 - ieeexplore.ieee.org
Bangladesh, as an agro-based nation, is facing a double burden: growing population,
increased food demand, and unprecedented use of fossil fertilizers. Artificial Neural Network …

Parallel attention-based LSTM for building a prediction model of vehicle emissions using PEMS and OBD

H Xie, Y Zhang, Y He, K You, B Fan, D Yu, B Lei… - Measurement, 2021 - Elsevier
Portable emission measurement system (PEMS) testing, which is the most accurate
measurement method for vehicle emissions, has been included into the regulations of …

[HTML][HTML] Explaining deep learning models for ozone pollution prediction via embedded feature selection

MJ Jiménez-Navarro, M Martínez-Ballesteros… - Applied Soft …, 2024 - Elsevier
Ambient air pollution is a pervasive global issue that poses significant health risks. Among
pollutants, ozone (O 3) is responsible for an estimated 1 to 1.2 million premature deaths …

Energy assessment and greenhouse gas predictions in the automotive manufacturing industry in Iran

P Javadi, B Yeganeh, M Abbasi… - Sustainable Production …, 2021 - Elsevier
The automotive manufacturing industry responsible for a large share of fuel and electricity
consumption and is a major source of greenhouse gasses emission. Considering the Global …