The Application of Wavelet Neural Network in Prediction of the Fish Price

Abstract

The market fish price is an important factor that affects the income of fishermen, so how to accurately analyze and predict the fish pricet o obtain huge profits has caught people's attention. As science advances, various price forecasting and analysis methods have come into being. How to build a prediction theories and models with relatively high success rate has been the study of many scholars over the years. With the development of artificial intelligence, neural networks have become an important tool of predicting and analyzing changes in market prices. Neural networks are important artificial intelligence technology, which have simple structures, but are able to solve complicated problems. They have strong applicability in predicting the mature index fluctuations in a short period. This paper considers some shortcomings and deficiencies the BP network prototype, which tries to use the wavelet Functions to replace the excitation function in the traditional BP algorithm on the basis of a network of neurons and then forms into WNN. We can verify the feasibility of WNN by perch price forecasts, and then this method is used in price forecasts of the three main fish of the Ulungur Lake Aquatic, to provide the basis for the aquatic base decision