Artificial neural network model for simulation of water distribution in sprinkle irrigation

Revista Brasileira de Engenharia Agrícola e Ambiental

Azevedo, Carlos A. V. de¹  Lima, Vera L. A. de¹  Eyng, Eduardo²  Dantas Neto, José¹  Menezes, Paulo L. de² 

[1] Universidade Federal de Campina Grande, Campina Grande, BR;Universidade Tecnológica Federal do Paraná, Medianeira, BR

关键词: sprinkler;    water distribution uniformity;    artificial intelligence;    computational model;   

DOI  :  10.1590/1807-1929/agriambi.v19n9p817-822

学科分类：农业科学（综合）

来源: Universidade Federal de Campina Grande * Centro de Ciencias e Tecnologia

【 摘 要 】

Determining uniformity coefficients of sprinkle irrigation systems, in general, depends on field trials, which require time and financial resources. One alternative to reduce time and expense is the use of simulations. The objective of this study was to develop an artificial neural network (ANN) to simulate sprinkler precipitation, using the values ​​of operating pressure, wind speed, wind direction and sprinkler nozzle diameter as the input parameters. Field trials were performed with one sprinkler operating in a grid of 16 x 16, collectors with spacing of 1.5 m and different combinations of nozzles, pressures, and wind conditions. The ANN model showed good results in the simulation of precipitation, with Spearman's correlation coefficient (rs) ranging from 0.92 to 0.97 and Willmott agreement index (d) from 0.950 to 0.991, between the observed and simulated values for ten analysed trials. The ANN model shows promise in the simulation of precipitation in sprinkle irrigation systems.

【 授权许可】

Unknown