Fuzzy Q learning algorithm for dual-aircraft path planning to cooperatively detect targets by passive radars

The problem of passive detection discussed in this paper involves searching and locating an aerial emitter by dualaircraft using passive radars. In order to improve the detection probability and accuracy, a fuzzy Q learning algorithrn for dual-aircraft flight path planning is proposed. The passive detection task model of the dual-aircraft is set up based on the partition of the target active radar＇s radiation area. The problem is formulated as a Markov decision process （MDP） by using the fuzzy theory to make a generalization of the state space and defining the transition functions, action space and reward function properly. Details of the path planning algorithm are presented. Simulation results indicate that the algorithm can provide adaptive strategies for dual-aircraft to control their flight paths to detect a non-maneuvering or maneu- vering target.

A NovelMethod for Determining Tourism Carrying Capacity in a Decision-Making Context Using q−Rung Orthopair Fuzzy Hypersoft Environment

Tourism is a popular activity that allows individuals to escape their daily routines and explore new destinations for various reasons,including leisure,pleasure,or business.A recent study has proposed a unique mathematical concept called a q−Rung orthopair fuzzy hypersoft set(q−ROFHS)to enhance the formal representation of human thought processes and evaluate tourism carrying capacity.This approach can capture the imprecision and ambiguity often present in human perception.With the advanced mathematical tools in this field,the study has also incorporated the Einstein aggregation operator and score function into the q−ROFHS values to supportmultiattribute decision-making algorithms.By implementing this technique,effective plans can be developed for social and economic development while avoiding detrimental effects such as overcrowding or environmental damage caused by tourism.A case study of selected tourism carrying capacity will demonstrate the proposed methodology.

Fuzzy Metrics Characterized by Molecules and Sets

Erceg in [1] extended the Hausdorff distance function betwen subsets of a set X to fuzzy settheory, and introduced a fuzzy pseudo-quasi-metric(p. q. metric) p: L^x xL^x -[0,∞] where L is acompletely distributive lattice, and the associated family of neighborhood mappings {Dr |r>O}. Thefuzzy metric space in Erceg's sense is denoted by (L^x, p, Dr) since there exists a one to one correspondence between fuzzy p. q. metrics and associatcd families of neighborhood mapping, a family{Dr|r>0}satisfying certain conditions is also callcd a (standard) fuzzy p. q metric. In [2] Liang defimed apointwise fuzzy p. q. metric d: P(L^x)×P(L^x)-[0, ∞) and applicd it to the construction of theproduct fuzzy metric. In this paper, we give axiomatic definitions of molcculewise and

区间集非交换剩余格〈∈,∈Q〉-广义fuzzy奇异滤子的构造与属性约简

基于区间集思想、滤子理论和广义奇异概念,引入了区间集非交换剩余格和区间集非交换剩余格广义奇异滤子的定义,提出了构造区间集非交换剩余格广义fuzzy奇异滤子与区间集非交换剩余格〈∈,∈Q〉-广义fuzzy奇异滤子的方法,并给出它们之间的递进式本质属性与区间集相对必要属性的关系,体现代数结构表达的多样性与相对独立性。

区间集非交换剩余格〈∈,∈凵Q〉-广义Fuzzy蕴涵滤子的构造性刻画

借鉴反映不确定性推理本质特征的滤子理论和用模糊粗糙集上、下近似集表述的区间集思想,引入了区间集非交换剩余格的概念,讨论构成区间集非交换剩余格的代数结构特征,构造性地给出了广义Fuzzy蕴涵滤子与其相应的〈∈,∈凵Q〉-广义Fuzzy蕴涵滤子间的等价性表示定理,体现了性质迥异的区间集非交换剩余格代数表示形式的内在相容性。