Chaotic Neural Network Model for Predicting Relative Humidity in Hotan of Xinjiang Autonomous Region
Shengying Qin · Zhongguo nongye qixiang · 2008
According to the insufficiency of a single index in identifying the chaotic character,the Hurst exponent,lyapunov exponent and saturated correlation dimensions were used to identify the chaotic characteristics of the relative humidity in Hotan.The chaotic neural network model was established.The monthly average relative humidity for the period of 1954-2002 was simulated and predicted for the period of 2003-2004.The average relative error was 2.96% for the simulation and 0.85% for the prediction respectively.The validation results indicated that the model had a relative high accuracy.