Research on civil aviation logistics forecasting based on fuzzy neural networks and simulation analysis

To plan the reform and expansion program of China's airport rationally,the civil aviation logistics forecasting is studied mainly from the perspective of passenger traffic volume,in view of the characteristics of our civil aviation. A fuzzy diagonal regression neural networks recurrent forecast model is proposed based on analyzing influential factors of passenger traffic volume. This model dealt with the uncertain factors fuzzily and certainty factors using normalization in the front network layer,which solved the problem for in-consistent of importing dimension effectively. Throughout the test of the actual data and the contrast with the forecasting results of the inner and outer recursion neural networks forecast model,the prediction precision is higher using this model predict civil aviation passenger volume. Moreover,the simulation system of civil aviation logistics forecasting is developed using visual basic to verify the fore-casting results,the experimental results show that the simulation system has well application prospect and the promoted value.