SIMULATING SPRINKLER DISTRIBUTION PATTERN
ARTIFICIAL NEURAL NETWORK
Versandkostenfrei!
Versandfertig in 6-10 Tagen
40,99 €
inkl. MwSt.
PAYBACK Punkte
20 °P sammeln!
Sprinkler distribution pattern is a key factor for the efficient use of an irrigation system. The ballistic method for simulation has been accepted by many researchers. This method requires a deep understanding of droplet dynamics. The purpose of this work is to present an ANN model that simulates the sprinkler distribution pattern at various wind speeds and operating conditions. Main input parameters for the ANN are Wind Speed, CV% of Wind Speed, Operating Pressure, Radial Distance of Grid Point, and Effective Angle of catch can. Using these five input parameters, the ANN structure is trained...
Sprinkler distribution pattern is a key factor for the efficient use of an irrigation system. The ballistic method for simulation has been accepted by many researchers. This method requires a deep understanding of droplet dynamics. The purpose of this work is to present an ANN model that simulates the sprinkler distribution pattern at various wind speeds and operating conditions. Main input parameters for the ANN are Wind Speed, CV% of Wind Speed, Operating Pressure, Radial Distance of Grid Point, and Effective Angle of catch can. Using these five input parameters, the ANN structure is trained and compared with observed data of the sprinkler distribution pattern. Out of 31311 data points, 80% were used for training the model, and 20% of the data were used for testing the trained models. The results revealed that the ANN structure (5-24-4-1) performed better than other ANN structures.
Andere Kunden interessierten sich für
