TY - GEN
T1 - Structure analysis of fuzzy node fuzzy graph and its application to sociometry analysis
AU - Uesu, Hiroaki
PY - 2008
Y1 - 2008
N2 - We could generally analyze the inexact information efficiently and investigate the fuzzy relation by applying the fuzzy graph theory. We would extend the fuzzy graph theory, and propose a fuzzy node fuzzy graph. And we transform it to a fuzzy graph by using T-norm family. In this paper, we would discuss about four subjects, (1) fuzzy node fuzzy graph, (2) new T-norm "quasi logical product", (3) decision analysis of the optimal fuzzy graph in the fuzzy graph sequence {G λ }. By using the fuzzy node fuzzy graph theory and this new T-norm, we could clarify the relational structure of fuzzy information, and by using the decision of an optimal level on a partition tree, we could analyze the clustering relation among nodes. Moreover, we would illustrate its practical effectiveness with the case study concerning sociometry analysis.
AB - We could generally analyze the inexact information efficiently and investigate the fuzzy relation by applying the fuzzy graph theory. We would extend the fuzzy graph theory, and propose a fuzzy node fuzzy graph. And we transform it to a fuzzy graph by using T-norm family. In this paper, we would discuss about four subjects, (1) fuzzy node fuzzy graph, (2) new T-norm "quasi logical product", (3) decision analysis of the optimal fuzzy graph in the fuzzy graph sequence {G λ }. By using the fuzzy node fuzzy graph theory and this new T-norm, we could clarify the relational structure of fuzzy information, and by using the decision of an optimal level on a partition tree, we could analyze the clustering relation among nodes. Moreover, we would illustrate its practical effectiveness with the case study concerning sociometry analysis.
KW - Fuzzy node fuzzy graph
KW - Sociometry analysis
KW - T-norm
UR - http://www.scopus.com/inward/record.url?scp=57749197554&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=57749197554&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-85567-5-11
DO - 10.1007/978-3-540-85567-5-11
M3 - Conference contribution
AN - SCOPUS:57749197554
SN - 3540855661
SN - 9783540855668
VL - 5179 LNAI
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 84
EP - 91
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
T2 - 12th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2008
Y2 - 3 September 2008 through 5 September 2008
ER -