CAJ | 학술논문

铁路分品类货运量预测是制定货运营销决策的依据。作者通过基础数据处理、构建微分方程、求解模型的时间响应方程3个步骤形成了灰色预测GM（1，1）模型的算法，同时介绍了模型检验方法。基于此，依据铁路1998-2010年的实际运量数据，预测得到2011、2012年铁路分品类货运量，进而对预测结果进行检验和分析，得到模型的适用性：即灰色模型对数据序列波动较少的品类预测效果较好，而数据序列波动性大的品类预测效果一般。最后，针对部分基础数据波动较大的序列，采用指数平滑法对灰色预测的结果进行修正，提高了总体的预测效果。
철로분품류화운량예측시제정화운영소결책적의거。작자통과기출수거처리、구건미분방정、구해모형적시간향응방정3개보취형성료회색예측GM（1，1）모형적산법，동시개소료모형검험방법。기우차，의거철로1998-2010년적실제운량수거，예측득도2011、2012년철로분품류화운량，진이대예측결과진행검험화분석，득도모형적괄용성：즉회색모형대수거서렬파동교소적품류예측효과교호，이수거서렬파동성대적품류예측효과일반。최후，침대부분기출수거파동교대적서렬，채용지수평활법대회색예측적결과진행수정，제고료총체적예측효과。
Different railway freight category volume forecast is a base for making freight marketing decision. A gray model algorithm was consisted of three steps: data processing, construction ofdifferential equation,solvingthe time response of the model equations. The model checking method was introduced.According to the actual traffic data of Chinese railway from 1998 to 2010, 2011-2012’s category cargo traffic volumes were predicted, and then,the prediction results were tested. The results showed that the prediction effect was better if the data sequence was less volatile. Finally, the forecast result of the grey model was amended with an exponential smoothing method for the case of fluctuation data sequence. The overall forecast effect was improved.