为了处理系统验证中大量存在的不确定性,国内学者将可能性理论引入到模型检测中,提出了广义可能性Kriple结构。广义可能性Kriple结构有着较好的应用前景,但有许多问题需要解决。其中的一个问题是,如何高效便捷地建立广义可能性Kriple结...为了处理系统验证中大量存在的不确定性,国内学者将可能性理论引入到模型检测中,提出了广义可能性Kriple结构。广义可能性Kriple结构有着较好的应用前景,但有许多问题需要解决。其中的一个问题是,如何高效便捷地建立广义可能性Kriple结构的数学模型。为了给广义可能性Kriple结构中的模糊事件提供一种便捷方便的建模方法,在建模的过程中引入具有三种否定的广义模糊集(Generalized Fuzzy Sets with Contradictory,Opposite and Medium negation,GFScom),给出了广义可能性Kriple结构中的模糊事件的建模方法。应用实例表明所提方法是有效、可行的。展开更多
This paper discusses a method for identifying states in a multistage Decision Making Problem in which an Indifferent Event is either predetermined or can be automatically derived after the fact. First, when they are p...This paper discusses a method for identifying states in a multistage Decision Making Problem in which an Indifferent Event is either predetermined or can be automatically derived after the fact. First, when they are pre-set, the amount of possible information about Indifferent Event tends to be large. Therefore, since the decision is risk tolerant, the Max-Product method of Tanaka et al. is used to calculate the expected utility possibility. Next, in the case of automatic derivation after the fact, the amount of information on the possibility of Indifferent Event is relatively small, so the expected utility possibility is derived using Zadeh’s Fuzzy Event Possibility Measure. Here, it is assumed that the setting of the utility function is independent of the information on the occurrence of the Indifferent Event and is identified by the decision maker by lot drawing using the certainty equivalence method. As a concrete example, we focus on the pass/fail decision of a recommendation test, which is a two choice question in the No-Data Problem, and illustrate the multistage state identification method. .展开更多
文摘为了处理系统验证中大量存在的不确定性,国内学者将可能性理论引入到模型检测中,提出了广义可能性Kriple结构。广义可能性Kriple结构有着较好的应用前景,但有许多问题需要解决。其中的一个问题是,如何高效便捷地建立广义可能性Kriple结构的数学模型。为了给广义可能性Kriple结构中的模糊事件提供一种便捷方便的建模方法,在建模的过程中引入具有三种否定的广义模糊集(Generalized Fuzzy Sets with Contradictory,Opposite and Medium negation,GFScom),给出了广义可能性Kriple结构中的模糊事件的建模方法。应用实例表明所提方法是有效、可行的。
文摘This paper discusses a method for identifying states in a multistage Decision Making Problem in which an Indifferent Event is either predetermined or can be automatically derived after the fact. First, when they are pre-set, the amount of possible information about Indifferent Event tends to be large. Therefore, since the decision is risk tolerant, the Max-Product method of Tanaka et al. is used to calculate the expected utility possibility. Next, in the case of automatic derivation after the fact, the amount of information on the possibility of Indifferent Event is relatively small, so the expected utility possibility is derived using Zadeh’s Fuzzy Event Possibility Measure. Here, it is assumed that the setting of the utility function is independent of the information on the occurrence of the Indifferent Event and is identified by the decision maker by lot drawing using the certainty equivalence method. As a concrete example, we focus on the pass/fail decision of a recommendation test, which is a two choice question in the No-Data Problem, and illustrate the multistage state identification method. .
