CAJ | 학술논문

为合理规划我国机场改扩建方案,针对目前民航业特点,从客运量的角度对民航物流预测进行研究,在综合分析影响客运量因素的基础上,提出了模糊对角回归神经网络滚动预测模型.此模型在前端网络处理层对不确定性因素进行模糊量化处理,对确定性因素进行归一化处理,有效地解决了模型输入量纲不一致的问题.通过实际数据的检验与内回归神经网络、外回归神经网络的预测结果相比较,证明应用此模型进行民航客运量预测有较高的预测精度.并在此基础上利用Visual Basic语言开发了民航物流预测仿真系统,对预测结果进行仿真验证,试验结果表明该仿真系统具有广阔的应用前景和推广价值.
위합리규화아국궤장개확건방안,침대목전민항업특점,종객운량적각도대민항물류예측진행연구,재종합분석영향객운량인소적기출상,제출료모호대각회귀신경망락곤동예측모형.차모형재전단망락처리층대불학정성인소진행모호양화처리,대학정성인소진행귀일화처리,유효지해결료모형수입량강불일치적문제.통과실제수거적검험여내회귀신경망락、외회귀신경망락적예측결과상비교,증명응용차모형진행민항객운량예측유교고적예측정도.병재차기출상이용Visual Basic어언개발료민항물류예측방진계통,대예측결과진행방진험증,시험결과표명해방진계통구유엄활적응용전경화추엄개치.
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 inconsistent 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 forecasting results, the experimental results show that the simulation system has well application prospect and the promoted value.