An improved grey neural network model for predicting transportation disruptions
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- 作者：Chunxia Liua ; b ; liucx1999@163.com" class="auth_mail" title="E-mail the corresponding author ; Tong Shua ; shutong@hnu.edu.cn" class="auth_mail" title="E-mail the corresponding author ; Shou Chena ; chenshou@hnu.edu.cn" class="auth_mail" title="E-mail the corresponding author ; Shouyang Wanga ; c ; sywang@amss.ac.cn" class="auth_mail" title="E-mail the corresponding author ; Kin Keung Laid ; e ; mskklai@cityu.edu.hk" class="auth_mail" title="E-mail the corresponding author ; Lu Ganf ; 532339537@qq.com" class="auth_mail" title="E-mail the corresponding author
- 关键词：Transportation disruptions ; GM(1 ; 1) model ; Neural network ; Prediction
- 刊名：Expert Systems with Applications
- 出版年：2016
- 出版时间：1 March 2016
- 年：2016
- 卷：45
- 期：Complete
- 页码：331-340
- 全文大小：402 K
文摘
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Market demand is highly unpredictable after transportation disruption.
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It designs an improved prediction model of grey neural networks.
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It determines the number of neurons in the input layer of BP neural networks.
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It tests the feasibility of the prediction model through case studies.
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It helps optimize inventory and production after transportation disruption.