TY - JOUR
T1 - A Method to Determine Generalized Basic Probability Assignment in the Open World
AU - Jiang, Wen
AU - Zhan, Jun
AU - Zhou, Deyun
AU - Li, Xin
N1 - Publisher Copyright:
© 2016 Wen Jiang et al.
PY - 2016
Y1 - 2016
N2 - Dempster-Shafer evidence theory (D-S theory) has been widely used in many information fusion systems since it was proposed by Dempster and extended by Shafer. However, how to determine the basic probability assignment (BPA), which is the main and first step in D-S theory, is still an open issue, especially when the given environment is in an open world, which means the frame of discernment is incomplete. In this paper, a method to determine generalized basic probability assignment in an open world is proposed. Frame of discernment in an open world is established first, and then the triangular fuzzy number models to identify target in the proposed frame of discernment are established. Pessimistic strategy based on the differentiation degree between model and sample is defined to yield the BPAs for known targets. If the sum of all the BPAs of known targets is over one, then they will be normalized and the BPA of unknown target is assigned to 0; otherwise the BPA of unknown target is equal to 1 minus the sum of all the known targets BPAs. IRIS classification examples illustrated the effectiveness of the proposed method.
AB - Dempster-Shafer evidence theory (D-S theory) has been widely used in many information fusion systems since it was proposed by Dempster and extended by Shafer. However, how to determine the basic probability assignment (BPA), which is the main and first step in D-S theory, is still an open issue, especially when the given environment is in an open world, which means the frame of discernment is incomplete. In this paper, a method to determine generalized basic probability assignment in an open world is proposed. Frame of discernment in an open world is established first, and then the triangular fuzzy number models to identify target in the proposed frame of discernment are established. Pessimistic strategy based on the differentiation degree between model and sample is defined to yield the BPAs for known targets. If the sum of all the BPAs of known targets is over one, then they will be normalized and the BPA of unknown target is assigned to 0; otherwise the BPA of unknown target is equal to 1 minus the sum of all the known targets BPAs. IRIS classification examples illustrated the effectiveness of the proposed method.
UR - http://www.scopus.com/inward/record.url?scp=84975159434&partnerID=8YFLogxK
U2 - 10.1155/2016/3878634
DO - 10.1155/2016/3878634
M3 - 文章
AN - SCOPUS:84975159434
SN - 1024-123X
VL - 2016
JO - Mathematical Problems in Engineering
JF - Mathematical Problems in Engineering
M1 - 3878634
ER -