# Toxic gas dispersion prediction for point source emission using deep learning method

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/toxic-gas-dispersion-prediction-for-point-source-emission-using-deep-learning/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Jing Ni,Hongbing Yang,Jun Yao,Zhiying Li,Ping Qin |
| Citations | 34 |
| DOI | 10.1080/10807039.2018.1526632 |
| Fields | Engineering,Environmental Science |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W2910979794 |
| Type | article |
| Year | 2019 |

## Paper authors

- [Hongbing Yang](https://scholariq.org/researchers/hongbing-yang/)

## Paper primary topic

- [Wind and Air Flow Studies](https://scholariq.org/topics/wind-and-air-flow-studies/)

## Paper topics

- [Wind and Air Flow Studies](https://scholariq.org/topics/wind-and-air-flow-studies/)
- [Fire Detection and Safety Systems](https://scholariq.org/topics/fire-detection-and-safety-systems/)
- [Air Quality Monitoring and Forecasting](https://scholariq.org/topics/air-quality-monitoring-and-forecasting/)

---
Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.