Forecasting SMEs’ credit risk in supply chain finance with an enhanced hybrid ensemble machine learning approach
Current Language EN
English English Türkçe Türkçe Español Español Português Português Pусский Pусский Filipino Filipino Tiếng Việt Tiếng Việt हिन्दी हिन्दी العربية العربية বাংলা বাংলা Deutsch Deutsch 中文 中文

Forecasting SMEs’ credit risk in supply chain finance with an enhanced hybrid ensemble machine learning approach

Zhu, Y.
international journal of production economics 2019 Vol. 211 pp. 22-33
318
zhu2019forecastinginternational

Access

DOI:
10.1016/j.ijpe.2019.01.032

Citation

ID: 48301
Ref Key: zhu2019forecastinginternational
Use this key to autocite in SciMatic or Thesis Manager

References

References

No Bibliography

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
48301
Unique Identifier:
10.1016/j.ijpe.2019.01.032
Network:
Scimatic Chain (ID: 481)
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
4/5
Blockchain Upload Locked

Complete all 5 checklist items to tokenize your article

Gas fees required in SCI Coins
Buy SCI

Saymatik Web3.0 Wallet

Google Play
App Store