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Researchers have known for some time that non-linearity exists in the financial markets and that neural networks can be used to forecast market returns. In this article, we present a novel stock market prediction system which focuses on forecasting the relative tendency growth between different stocks and indices rather than purely predicting their values. This research utilizes artificial neural...
Inflation is one of the most important macroeconomic variables. However, the behavior of inflation is so complicated that both economists and statisticians have strived to model and forecast inflation for years. In this study, the linear AS-AD model and nonlinear artificial neural network (ANN) technique are both employed to have a better understanding of the inflation behavior in China from 1992...
Urbanization is the general trend and tide of the current world development and also one of the most remarkable social and economical phenomena in the world. Urbanization level becomes an important symbol of the economic strength and modernization level in a region and thus how to improve the local urbanization level has become a priority for economic development. With the increasing urbanization...
Based on the idea of nonlinear prediction of phase space reconstruction, this paper presented a time delay BP neural network model, whose generalization capability was improved by Bayesian regularization. Furthermore, the model is applied to forecast the imp&exp trades in one industry. The results showed that the improved model has excellent generalization capabilities, which not only learned...
It is difficult to accurately analyze forecasting of tax income. This thesis establishes a tax forecasting model based on BP neural network to analyze impacts imposed on tax income by changes of the following economic factors: industrial added value, total investment in fixed assets, total volume of import and export, total volume of fiscal expenditure, resident consumption level, etc. The thesis...
An effective foreign exchange (Forex) trading decision is usually dependent on effective forex forecasting. This paper reports empirical evidence that an artificial neural network (ANN) is applicable to the prediction of foreign exchange rates. The architecture of the network and the related algorithms are described. The effects of the choice of inputs into a neural network model are examined. Except...
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