Evidence map›Paper›PMID 38894255›Full record

ArticleSensors (Basel, Switzerland)2024

A Study on Predicting the Deviation of Jet Trajectory Falling Point under the Influence of Random Wind.

Hengyu Cheng, Jinsong Zhu, Sining Wang, Ke Yan, Haojie Wang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Hengyu ChengSchool of Mechanical and Electrical Engineering, China University of Mining and Technology, Xuzhou 221006, China.
Jinsong ZhuSchool of Mechanical and Electrical Engineering, China University of Mining and Technology, Xuzhou 221006, China.
Sining WangSchool of Mechanical and Electrical Engineering, China University of Mining and Technology, Xuzhou 221006, China.
Ke YanSchool of Mechanical and Electrical Engineering, China University of Mining and Technology, Xuzhou 221006, China.
Haojie WangSchool of Mechanical and Electrical Engineering, China University of Mining and Technology, Xuzhou 221006, China.

Funding

Innovative Research Group Project of the National Natural Science Foundation of China 2022YFC3090502,52204256.
6 · The paper itself

Abstract

As one of the main external factors affecting the fire extinguishing accuracy of sprinkler systems, it is necessary to analyze and study random wind. However, in practical applications, there is little research on the impact of random wind on sprinkler fire extinguishing points. To address this issue, a new random wind acquisition system was constructed in this paper, and a method for predicting jet trajectory falling points in Random Forest (RF) under the influence of random wind was proposed, and compared with the commonly used prediction model Support Vector Machine (SVM). The method in this article reduces the error in the x direction of the 50 m prediction result from 2.11 m to 1.53 m, the error in the y direction from 0.64 m to 0.6 m, and the total mean absolute error (MAE) from 31.3 to 23.5. Simultaneously, predict the falling points of jet trajectory at different distances under the influence of random wind, to demonstrate the feasibility of the proposed method in practical applications. The experimental results show that the system and method proposed in this article can effectively improve the influence of random wind on the falling points of a jet trajectory. In summary, the image acquisition system and error prediction method proposed in this article have many potential applications in fire extinguishing.

Indexed as

jet trajectorymodel predictionrandom forestrandom wind

Identifiers

PMID38894255
PMCPMC11174715

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