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

**Type:** Papers  
**Canonical URL:** https://picoportal.org/library/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://picoportal.org/library/researchers/hongbing-yang/)

## Paper journal

- [Human and Ecological Risk Assessment An International Journal](https://picoportal.org/library/journals/human-and-ecological-risk-assessment-an-international-journal/)

## Paper primary topic

- [Wind and Air Flow Studies](https://picoportal.org/library/topics/wind-and-air-flow-studies-2/)

## Paper topics

- [Wind and Air Flow Studies](https://picoportal.org/library/topics/wind-and-air-flow-studies-2/)
- [Fire Detection and Safety Systems](https://picoportal.org/library/topics/fire-detection-and-safety-systems/)
- [Air Quality Monitoring and Forecasting](https://picoportal.org/library/topics/air-quality-monitoring-and-forecasting/)

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Source: PICO Portal — public research metadata, principally OpenAlex. See https://picoportal.org/library/sources/ for provenance and https://picoportal.org/library/methodology/ for what these figures mean.