2022
DOI: 10.3389/fbuil.2022.945615
|View full text |Cite
|
Sign up to set email alerts
|

Forecasting the Amount of Traffic-Related Pollutant Emissions by Neural Networks

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
2
0

Year Published

2023
2023
2025
2025

Publication Types

Select...
3
2
1

Relationship

1
5

Authors

Journals

citations
Cited by 7 publications
(2 citation statements)
references
References 31 publications
0
2
0
Order By: Relevance
“…The mathematical expression of the output and input of the neurons in this model is as follows [11][12][13] .…”
Section: Figure 5 Structure Diagram Of Neural Networkmentioning
confidence: 99%
“…The mathematical expression of the output and input of the neurons in this model is as follows [11][12][13] .…”
Section: Figure 5 Structure Diagram Of Neural Networkmentioning
confidence: 99%
“…Given the difficult natural and climatic conditions of the Arctic region, there is a high risk of transport accidents of various types that can potentially threaten the environment, the population and the entire ecosystem of coastal areas. The authors of [75] propose to create an intelligent decision support system that would allow for detecting traffic accidents, predicting their development and justifying appropriate operational decisions.Additionally, the authors describe the implementation of the elements of such an intelligent system, which allows for predicting the volume of environmental load [76] and optimizing traffic light operation modes [77].…”
Section: Itc and Green Logisticsmentioning
confidence: 99%