Back to Search
Start Over
Predicting logistics delivery demand with deep neural networks
- Source :
- 2018 7th International Conference on Industrial Technology and Management (ICITM).
- Publication Year :
- 2018
- Publisher :
- IEEE, 2018.
-
Abstract
- Delivery time affects the logistics route, depending on the needs of the place and quantity. An efficient prediction of delivery demand would help the construction of logistics model. The data on delivery demand are time-dependency and space-correlation. Modeling the multidimensional sequence or making the prediction based on it would be a computation consuming work. Our research is based on deep learning to propose an efficient procedure to predict delivery demand. With the simulation study, the prediction performance of the proposed procedure is acceptable. This is conducive to the further study of logistics decisions making.
- Subjects :
- 0209 industrial biotechnology
Sequence
021103 operations research
business.industry
Computer science
Deep learning
Computation
0211 other engineering and technologies
02 engineering and technology
Machine learning
computer.software_genre
020901 industrial engineering & automation
Work (electrical)
Deep neural networks
Artificial intelligence
business
computer
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2018 7th International Conference on Industrial Technology and Management (ICITM)
- Accession number :
- edsair.doi...........40c546e2de57cf1bf9e483bab9db8cea