Minor losses in start connectors of microirrigation laterals

Prediction of Pressure–Discharge Curves of Trapezoidal Labyrinth Channels from Nonlinear Regression and Artificial Neural Networks

“…Nonlinear regression was evaluated as one of the approaches for modeling emitter discharge. Nonlinear regression models based on the power law have been used successfully to model hydraulic phenomena (Perboni et al 2015;Vekariya et al 2010;Vilaça et al 2017;Zitterell et al 2013). For a steady water temperature, it was assumed that the labyrinth discharge was influenced mostly by the labyrinth geometry and the operating pressure.…”

“…The RMSE is a common index to measure the accuracy of models (Duran-Ros et al 2010;Provenzano et al 2016) that quantifies differences between estimated and observed values and also makes it possible to compare the performances of models. Graphical error analysis also was performed to evaluate the accuracy of the predictions, and it was a useful tool to quantify prediction errors associated with the frequency of occurrence (Sobenko et al 2018;Vilaça et al 2017).…”

“…When several potential predictors are available, the selection of variables required to build a model represents a frequent problem in regression analysis related to hydraulics (Vilaça et al 2017). Unnecessary predictors included in the model complicate the description of the process and may result in poor predictions, whereas omitting important effects may reduce predictive power (Chatterjee and Simonoff 2013).…”

Study on Permeability Stability of Sand-Based Microporous Ceramic Filter Membrane

“…To facilitate calculations, the internal water flow channel of the microporous ceramic was simplified into an equal-diameter circular tube model to analyze the hydraulic characteristics. Therefore, the loss of water flow during the flow was mainly the resistance loss along the path: h f = λlv 2 /2 gd [31]. The resistance coefficient λ was positively correlated with roughness.…”

Development of sprinkler with adjustable orifice using iris-type mechanism for variable rate irrigation

“…The RMSE is a common index to measure the accuracy of models that quantify differences between observed and estimated values (Duran-Ros et al, 2010;Provenzano et al, 2015). The graphical error analysis is also useful to quantify prediction errors while evaluating the accuracy of models because it provides prediction errors associated with their frequency of occurrence (Vilaça et al, 2017). The relationship between flow and pressure is one of the hydraulic characteristics that directly influences the performance of an irrigation system (Frizzone et al, 2012).…”