Analysis of Comprehensive Artificial Neural Network Computer Media Aided Construction of Economic Forecasting Model

Abstract

As a complex system engineering, economic forecasting involves many fields and disciplines, and its accuracy largely depends on the selected forecasting method and forecasting model. The construction of the traditional economic prediction model mainly depends on the theories of economic statistics and metrology, which cannot meet the prediction needs of the new era. ANN model has a more flexible nonlinear quality and learning mode so that it can effectively adapt to the prediction scenario of a nonlinear economic system. ANN is an abstract model of the human brain neuronal network based on the information-processing perspective and composed of different networks to achieve a specific representation of logical strategies. ANN’s self-learning function, associative storage function, and the ability to find optimal solutions at high speed have led to its in-depth application and research in an increasing number of fields. In addition, ANN research work has continued to advance, has made great progress in many fields represented by economic forecasting, has successfully solved many practical problems, showing a more intelligent adaptation in the field of economics, and therefore has an important research value. Based on this, this paper first analyzes the economic system prediction, then studies the ANN medium model and learning algorithm, and finally verifies the effectiveness of the ANN economic prediction model integrating computer medium.