关键词: 免疫人工鱼群算法, BP神经网络, 经济预测

Abstract: In view of the weaknesses of BP neural network for economic forecasting，a new and more effective economic forecasting model called Immune Artificial Fish Swarm Algorithm Neural Network（IAFSANN） is developed.IAFSANN can improve the precision of learning，convergence rate and generalization ability through training neural networks，furthermore can overcome the shortcomings of BP neural network to some degree.According to the economic data of Zhanjiang，Guangdong，neural networks have been trained by adopting IAFSA to build an IAFSA-NN，which is realized by MATLAB 7.0 and employed to forecast GDP.The forecasting results are satisfactory，proving that IAFSANN is superior to BP neural network.Meanwhile，IAFSANN turns out to be valid and feasible for economic forecasting.

Key words: immune artificial fish swarm algorithm, Back Propagation（BP） neural network, economic forecasting