A predictive model for flow index performance of pit drip irrigation emitters using BP-PSO algorithm
Weixiong Xu, Jiatong Jiang, Tianyu Xu · 2026
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Description
Weixiong Xu and two colleagues built in 2026 a neural network model to predict the flow index of pit drip irrigation emitters, a key design parameter. They tested a plant-inspired emitter design, gathering 160 training-testing points and 25 external validation points across pit depth, spacing, channel angle, and aperture.
Among four network variants, the particle-swarm-optimised two-hidden-layer model performed best, beating six rival machine learning methods and holding accuracy above 0.85 on external data. Aperture mattered most for the flow index, followed by angle, spacing, and depth. The model offers designers a reliable shortcut during emitter development.
Catalog record
| CREATOR | Weixiong Xu, Jiatong Jiang, Tianyu Xu |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 86 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |