In previous studies, an isosceles triangular-type possibility distribution was employed to represent the analog waves of a Gaussian Process. The model was then projected onto actual waves using Zadeh’s extension prin...In previous studies, an isosceles triangular-type possibility distribution was employed to represent the analog waves of a Gaussian Process. The model was then projected onto actual waves using Zadeh’s extension principle of mapping (Hori et al., 2019). Furthermore, by applying Vague Set and Systems theory, it was shown that the actual waves followed a Gaussian process, and that the system could be efficiently controlled via Monte Carlo simulation. However, due to the use of fuzzy OR logic in the extension principle of mapping and wave synthesis, the resulting ambiguity increased significantly. To address this issue, a Possibility Markov Chain was proposed, incorporating possibility theory to mitigate the explosion of ambiguity. In this study, we propose a novel modeling approach that utilizes a possibility transition matrix without relying on fuzzy OR logic. Additionally, we introduce the Sea-Control Algorithm, which artificially introduces system error into the system function, thereby enabling modification of the possibility transition matrix through the deliberate manipulation of possibility information within the fuzzy system.展开更多
文摘In previous studies, an isosceles triangular-type possibility distribution was employed to represent the analog waves of a Gaussian Process. The model was then projected onto actual waves using Zadeh’s extension principle of mapping (Hori et al., 2019). Furthermore, by applying Vague Set and Systems theory, it was shown that the actual waves followed a Gaussian process, and that the system could be efficiently controlled via Monte Carlo simulation. However, due to the use of fuzzy OR logic in the extension principle of mapping and wave synthesis, the resulting ambiguity increased significantly. To address this issue, a Possibility Markov Chain was proposed, incorporating possibility theory to mitigate the explosion of ambiguity. In this study, we propose a novel modeling approach that utilizes a possibility transition matrix without relying on fuzzy OR logic. Additionally, we introduce the Sea-Control Algorithm, which artificially introduces system error into the system function, thereby enabling modification of the possibility transition matrix through the deliberate manipulation of possibility information within the fuzzy system.
