TY - GEN
T1 - Regression model based on fuzzy random variables
AU - Imai, Shinya
AU - Wang, Shuming
AU - Watada, Junzo
PY - 2008
Y1 - 2008
N2 - In real-world regression problems, various statistical data may be linguistically imprecise or vague. Because of such co-existence of random and fuzzy information, we can not characterize the data only by random variables. Therefore, one can consider the use of fuzzy random variables as an integral component of regression problems. The objective of this paper is to build a regression model based on fuzzy random variables. First, a general regression model for fuzzy random data is proposed. After that, using expected value operators of fuzzy random variables, an expected regression model is established. The expected regression model can be developed by converting the original problem to a task of a linear programming problem. Finally, an explanatory example is provided.
AB - In real-world regression problems, various statistical data may be linguistically imprecise or vague. Because of such co-existence of random and fuzzy information, we can not characterize the data only by random variables. Therefore, one can consider the use of fuzzy random variables as an integral component of regression problems. The objective of this paper is to build a regression model based on fuzzy random variables. First, a general regression model for fuzzy random data is proposed. After that, using expected value operators of fuzzy random variables, an expected regression model is established. The expected regression model can be developed by converting the original problem to a task of a linear programming problem. Finally, an explanatory example is provided.
KW - Expected value
KW - Fuzzy random variable
KW - Fuzzy regression model
UR - http://www.scopus.com/inward/record.url?scp=57749189766&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=57749189766&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-85567-5-17
DO - 10.1007/978-3-540-85567-5-17
M3 - Conference contribution
AN - SCOPUS:57749189766
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 - 127
EP - 135
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 -