Growth Enterprises Identification with Artificial Intelligence
- DOI
- 10.2991/icmcs-18.2018.37How to use a DOI?
- Keywords
- Artificial intelligence; Logistics industry; Growth potential; Random forest
- Abstract
The rise of big data and artificial intelligence has revolutionized many industries, including logistics. From the long-term development of the enterprise, growth plays an important role. Based on the 222 observations from logistics enterprises, two kinds of strategies are adopted and machine learning algorithm models such as artificial neural network, support vector machine and random forest are employed. To sum up, on one hand, it is feasible to establish growth index by reducing dimension with principal component analysis then classify on growth financial indicators. On the other hand, by comparison, the random forest algorithm model can identify the growth state of the enterprise in accuracy.
- Copyright
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Liang Wang PY - 2018/10 DA - 2018/10 TI - Growth Enterprises Identification with Artificial Intelligence BT - Proceedings of the 8th International Conference on Management and Computer Science (ICMCS 2018) PB - Atlantis Press SP - 185 EP - 189 SN - 2352-538X UR - https://doi.org/10.2991/icmcs-18.2018.37 DO - 10.2991/icmcs-18.2018.37 ID - Wang2018/10 ER -