Abstract
The purpose of this study is to provide a scientific research and operation paradigm for the risk assessment in the early development of state-level new areas, in order to facilitate risk identification, assessment and management of national new districts especially Xiongan New Area. Finally, it constructs a national district risk index system including six risk factors and 23 risk indicators. It is found that the three factors with the highest comprehensive weight include the risk of the departure from the development, risk of sustainable development and green risk. The smallest risk is found in Shanghai Pudong New Area and Tianjin Binhai New Area, while the biggest risk is in the Shaanxi Xixian New Area and Gansu Lanzhou New Area. The fuzzy comprehensive evaluation model put forward in this paper overcomes the defects of the traditional fuzzy comprehensive evaluation model, fully considering the fuzziness and uncertainty of the evaluation indicators of risk under the background of big data, and also considering the fuzziness of human judgment. At the same time, it can expand the usage of the result information through the change of the maximum membership degree principle, so that it has broad application value.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Zeng, M., Chen, Y.J., Xian-Zhong, H.U., et al.: The risk assessment of China’s smart grid based on multi-level fuzzy comprehensive evaluation method. East China Electric Power 4, 536–538 (2011)
Wei, G., Zhang, X., Zhang, X.: Research on risk assessment and optimization control of information systems development: based on improved fuzzy comprehensive evaluation and dynamic programming algorithm. In: 6th International Conference on Wireless Communications Networking and Mobile Computing (WiCOM), IEEE, 2010, pp. 1–5
Han, L., Song, Y., Duan, L., et al.: Risk assessment methodology for Shenyang Chemical Industrial Park based on fuzzy comprehensive evaluation. Environ. Earth Sci. 73(9), 5185–5192 (2015)
Zheng-Jie, X.U., Zhang, Y.P., Hong-Sheng, S.U.: Application of risk assessment on fuzzy comprehensive evaluation method based on the cloud model. J. Saf. Environ. 4, 69–72 (2014)
Zhang, K.W.: Risk assessment of smart grid cyber security based on multi-level fuzzy comprehensive evaluation method. Adv. Mater. Res. 605–607, 2311–2317 (2013)
Zhou, R.F., Ling-Ling, G.E.: Research on hotel supply chain risk assessment based on fuzzy comprehensive evaluation method. Logist. Eng. Manag. 8, 32 (2014)
Xinyuan, J.: Credit risk assessment model of SMEs based on multi-level fuzzy comprehensive evaluation: a leather factory in Wenzhou as an example. Risti Iberian J. Inf. Syst. Technol. (2016)
Li, Y., Wang, W., Liu, B.X., et al.: Research on oil spill risk of port tank zone based on fuzzy comprehensive evaluation. Aquat. Proc. 3, 216–223 (2015)
Xu, Y.G., Lv, P.: Research on the risk assessment of IPD mode based on the fuzzy comprehensive evaluation. Appl. Mech. Mater. 457–458, 1181–1184 (2014)
Yang, P., Wang, T.: EPC project risk assessment based on the improved fuzzy comprehensive evaluation algorithm. J. Converg. Inf. Technol. 8(5), 710–716 (2013)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Chen, Y., Chai, H. & Huang, Y. Research on risk assessment in the early development of state-level new areas based on the improved fuzzy comprehensive evaluation model. Cluster Comput 22 (Suppl 2), 3431–3444 (2019). https://doi.org/10.1007/s10586-018-2190-3
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10586-018-2190-3