TY - CHAP
T1 - An evolutionary programming based knowledge ensemble model for business risk identification
AU - Yu, Lean
AU - Lai, Kin Keung
AU - Wang, Shouyang
PY - 2008
Y1 - 2008
N2 - Business risk identification is one of the most important components in business risk management. In this study, a knowledge ensemble methodology is proposed to design an intelligent business risk identification system, which is composed of two procedures. First of all, some data mining and knowledge discovery algorithms are used to explore the implied knowledge about business risk hidden in the business data. Then the implied knowledge generated from different mining algorithms is aggregated into an ensemble output using an evolutionary programming (EP) technique. For verification, the knowledge ensemble methodology is applied to a real-world business risk dataset. The experimental results reveal that the proposed intelligent knowledge ensemble methodology provides a promising solution to business risk identification. © 2008 Springer-Verlag Berlin Heidelberg.
AB - Business risk identification is one of the most important components in business risk management. In this study, a knowledge ensemble methodology is proposed to design an intelligent business risk identification system, which is composed of two procedures. First of all, some data mining and knowledge discovery algorithms are used to explore the implied knowledge about business risk hidden in the business data. Then the implied knowledge generated from different mining algorithms is aggregated into an ensemble output using an evolutionary programming (EP) technique. For verification, the knowledge ensemble methodology is applied to a real-world business risk dataset. The experimental results reveal that the proposed intelligent knowledge ensemble methodology provides a promising solution to business risk identification. © 2008 Springer-Verlag Berlin Heidelberg.
KW - Artificial neural network
KW - Business risk identification
KW - Data mining
KW - Evolutionary programming
KW - Knowledge ensemble
KW - Logit regression analysis
KW - Multivariate discriminant analysis
KW - Soft computing
KW - Support vector machines
UR - http://www.scopus.com/inward/record.url?scp=42349103095&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-42349103095&origin=recordpage
U2 - 10.1007/978-3-540-79005-1_4
DO - 10.1007/978-3-540-79005-1_4
M3 - RGC 12 - Chapter in an edited book (Author)
SN - 9783540790044
VL - 230
T3 - Studies in Fuzziness and Soft Computing
SP - 57
EP - 72
BT - Soft Computing Applications in Business
ER -