Impact of Trade Protectionism on Economic Growth Based on Bayesian Networks and Fuzzy Logic

Abstract

A government policy known as trade protectionism limits international trade in order to support home industries. Since the global financial crisis, the country's economy has seen a slowdown in trade growth. The data is taken from the China Census Bureau (CCB) and after the data is fed in to data processing technique our proposed is Adaptive Square Root Cubature Kalman Filter (ASRCKF). The preprocessed data is fed into the Bayesian Networks (BN) decision making activities in different influencing factors to foreign trade protectionism and uses fuzzy logic (FL) analyze the China’s foreign trade Protectionism. Set of data is-processing-decision making activities in which actual data using Bayesian networks and fuzzy logic are combined in the Trade Protectionism. The proposed model is implemented in MATLAB/ Simulink platform and the accuracy is compared to various existing approaches such as Particle Optimization Algorithm (POA) Radial Basis Function (RBF) and Support vector neural network (SVNN) method our proposed method obtains 98% of accuracy.