Research on Forecast of Sugar Price Based on Improved Neural Network

According to the feature of market fluctuations in the price of sugar, an optimization algorithm based on improved genetic neural network training was proposed in this paper. A population optimization model on adaptive crossover and mutation operator and niche was designed, by applying gray theory and technology, the sugar price data was processed. A multi-dimensional learning sample and teacher sample for improved genetic neural network training was constructed. Finally, the trend of sugar prices of 1-2 weeks in year 2008 to 2009 was predicted by cases, the comparison of the forecast algorithm versus gray linear systems, S-BP, SGA-BP algorithm showed the integrated optimization of forecast accuracy and forecast effect.