ArticleScientific reports2026
A predictive model for flow index performance of pit drip irrigation emitters using BP-PSO algorithm.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
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Authors and funding
3 authors.
Funding
Abstract
It is crucial to accurately obtain the flow index in designing and developing labyrinth drip irrigation emitters. This study designed a pit drip irrigation emitter based on plant biomimetic principles, and created training-testing datasets (160 data points) and external validation datasets (25 data points) through experiments. The improved backpropagation neural network (BP) regression algorithm based on particle swarm optimization (PSO) is used to predict the flow index of the pit drip irrigation emitter. The input parameters include the pit depth l, the inner and outer boundary spacing h, the flow channel angle θ, and the pit aperture j. There were four combinations with the different hidden layer settings, namely BP
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