TY - CHAP
T1 - Expected Value Model
AU - Li, Xiang
N1 - Publisher Copyright:
© 2013, Springer-Verlag Berlin Heidelberg.
PY - 2013
Y1 - 2013
N2 - Expected value of a fuzzy variable is the weighted average of all possible values in the sense of credibility measure, which is one of the most well-known credibilistic mappings for ranking fuzzy variables. Based on the concept of expected value, Liu and Liu proposed an expected value model, which had been widely used in many real-life applications. This chapter mainly introduces the concepts of expected value, variance, skewness, moment, as well as the fuzzy simulation technique, expected value model and applications in fuzzy portfolio analysis.
AB - Expected value of a fuzzy variable is the weighted average of all possible values in the sense of credibility measure, which is one of the most well-known credibilistic mappings for ranking fuzzy variables. Based on the concept of expected value, Liu and Liu proposed an expected value model, which had been widely used in many real-life applications. This chapter mainly introduces the concepts of expected value, variance, skewness, moment, as well as the fuzzy simulation technique, expected value model and applications in fuzzy portfolio analysis.
KW - Credibility Measure
KW - Expected Value Model
KW - Fuzzy Simulation Technique
KW - Fuzzy Variables
KW - Joint Acceptance Function
UR - https://www.scopus.com/pages/publications/85125858721
U2 - 10.1007/978-3-642-36376-4_3
DO - 10.1007/978-3-642-36376-4_3
M3 - Chapter
AN - SCOPUS:85125858721
T3 - Uncertainty and Operations Research
SP - 45
EP - 71
BT - Uncertainty and Operations Research
PB - Springer Nature
ER -