Abstract
Uemura (1991) discovered the mapping formula for Type 1 Vague events and presented an alternative problem as an example of its application. Since it is well known that the alternative problem leads to sequential Bayesian inference, the flow of subsequent research was to make the mapping formula multidimensional, to introduce the concept of time, and to derive a Markov (decision) process. Furthermore, we formulated stochastic differential equations to derive them. (Hori et.al (2019)) This paper refers to type 2 vague events based on a second-order mapping equation. This quadratic mapping formula gives a certain rotation by transforming a non-mapping function by a relation between two mapping functions. In addition, the derivation of the Type 2 Vague Markov process and the possibility factor analysis for the rotation are mentioned, based on the possibility theory.
