Recognition of Trade Barrier Based on General RBF Neural Network

Trade barriers correct externalities, but distort trade as well, which brings negative effect on international distribution of resources. Study on how to recognize there are trade barriers or would-be threat of trade barriers in international trade is of great necessity. Based on previous studies, taking horticultural products as an example, this paper designs a general RBF neural network model to detect whether there are trade barriers among the main destinations of Chinese horticultural products. The study shows that general RBF neural network can identify trade barriers correctly with an error probability about 10%, so it is a helpful tool for identification of trade barriers.