Analysis Based on RBF Neural Network for Effect of Artificial Flow Field on Dissolved Oxygen Uniform Distribution

Abstract

Abstract-To verify the effect of artificial flow on the improvement of local DO(dissolved oxygen) imbalance distribution, Lake Jing in Guangxi University was taken as the experimental area, five groups of experiments were designed, pump with different flow rate and different nozzle were used to push flow in experimental area, RBF Neural Network which is widely used in geographic information prediction was used to fitting the spatial distribution of dissolved oxygen and the dispersion coefficient was taken as the equilibrium index of DO horizontal distribution to analysis the effect of flow. The result shows that100 m 3 /min, 130 m 3 /min, 180 m 3 /min pump with circular nozzle and 130L/min pump with duckbill nozzle respectively need 1.5 hour, 1.0 hour, 0.5 hour, 1.5 hour to decrease the DO dispersion coefficient from 0.3 to 0.05, witch prove push flow has obvious effect on improving the DO balance and the effect is related with flow rate and nozzle, a larger flow pump and circular nozzle is preferred.

On the suitability of generalized regression neural networks for GNSS position time series prediction for geodetic applications in geodesy and geophysics

“…Neural networks and machine learning algorithms have been established as powerful and promising methods that have widespread applications in various fields, such as economics [17], fluid dynamics [16], stock market [17,6] and alike. These methods can be used for different purposes, including classification, prediction, the so-called regime switching, and asynchronous sampling [20].…”