[HTML][HTML] Machine learning predictions for carbon monoxide levels in urban environments

MA Almubaidin, NS binti Ismail, SD Latif… - Results in …, 2024 - Elsevier
The increasing carbon emissions in Malaysia necessitate accurate methods to track and
control pollution levels. This study focuses on predicting carbon monoxide (CO) …

Understanding and estimating the carbon dioxide emissions for urban buses at different road locations: A comparison between new-energy buses and conventional …

Y Pan, F Qiao, K Tang, S Chen, SV Ukkusuri - Science of the Total …, 2020 - Elsevier
Public transport buses are heavy-duty vehicles that travel through the city from morning till
night, which emits a large number of greenhouse gases. Understanding and estimating the …

Predicting ship fuel consumption based on LSTM neural network

Y Zhu, Y Zuo, T Li - 2020 7th International Conference on …, 2020 - ieeexplore.ieee.org
With the rapid development of marine trade and transportation, a large number of ships sail
at sea. The ship energy conservation and environment protection are becoming public …

Prediction and Comparison of In-Vehicle CO2 Concentration Based on ARIMA and LSTM Models

J Han, H Lin, Z Qin - Applied Sciences, 2023 - mdpi.com
An increase in the carbon dioxide (CO2) concentration within a vehicle can lead to a
decrease in air quality, resulting in numerous adverse effects on the human body. Therefore …

Deep learning LSTM recurrent neural network model for prediction of electric vehicle charging demand

J Shanmuganathan, AA Victoire, G Balraj, A Victoire - Sustainability, 2022 - mdpi.com
The immense growth and penetration of electric vehicles has become a major component of
smart transport systems; thereby decreasing the greenhouse gas emissions that pollute the …

The prediction of carbon emission information in Yangtze River economic zone by deep learning

H Huang, X Wu, X Cheng - Land, 2021 - mdpi.com
This study aimed to respond to the national “carbon peak” mid-and long-term policy plan,
comprehensively promote energy conservation and emission reduction, and accurately …

Predicting the environmental change of carbon emission patterns in South Asia: a deep learning approach using BiLSTM

M Aamir, MA Bhatti, SU Bazai, S Marjan, AM Mirza… - Atmosphere, 2022 - mdpi.com
China's economy has made significant strides in the past three decades. As a direct result of
China's “one belt, one road”(OBOR) initiative, the country's rate of industrialization and …

Instantaneous CO2 emission modelling for a Euro 6 start-stop vehicle based on portable emission measurement system data and artificial intelligence methods

M Mądziel - Environmental Science and Pollution Research, 2024 - Springer
One of the increasingly common methods to counteract the increased fuel consumption of
vehicles is start-stop technology. This paper introduces a methodology which presents the …

A deep learning method for monitoring vehicle energy consumption with gps data

K Ko, T Lee, S Jeong - Sustainability, 2021 - mdpi.com
A monitoring method for energy consumption of vehicles is proposed in the study. It is
necessary to have parameters estimating fuel economy with GPS data obtained while …

Air pollution prediction by deep learning model

S Jeya, L Sankari - 2020 4th International Conference on …, 2020 - ieeexplore.ieee.org
The impact of harmful pollutants in the air on human health is a vast area of research,
preventing or controlling, and also monitoring the pollutant is the huge responsibility of any …