A novel approach of three-way decisions with information interaction strategy for intelligent decision making under uncertainty
A novel approach of three-way decisions with information interaction strategy for intelligent decision making under uncertainty
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DOI：
10.1016/j.ins.2021.09.037
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发表时间：
2021-09-22
影响因子：
8.1
通讯作者：
Xu, Zeshui
中科院分区：
文献类型：
--
作者：
Liang, Decui;Wang, Mingwei;Xu, Zeshui
作为一种处理不确定决策的有效工具，三向决策在许多应用中得到了广泛的关注。决策理论粗糙集(DTRSS)作为TWD的经典模型，包含条件概率和损失函数两个关键元素。在本文中，我们通过信息交互和修改策略对这两个元素的确定进行了深入的研究，并进一步提出了一种新的TWD模型。首先，利用模糊c-均值(FCM)分别对状态属性信息和损失函数信息进行聚类。考虑到两类信息的交互作用，我们设计了相应的融合策略，对这些聚类结果进行融合，得到等价类，并提出了一种新的条件概率计算方法。然后，使用概率犹豫模糊集(P-HFSS)对同一等价类中不同成员的损失函数进行聚合，得到概率犹豫模糊元(P-HFES)损失函数。在这种情况下，P-HFSS不仅反映了决策者的犹豫不决的情况，还描绘了不同意见的比例。对于P-HFES损失函数，我们还详细研究了其异常值的修正方法。此外，在P-HFES损失函数的基础上，提出了概率犹豫模糊决策理论粗糙集(P-HFDTRSS)。最后，为了验证所提方法的有效性，我们进行了一系列的对比实验，并讨论了在六个UCI数据集上的决策结果。(C)2021 Elsevier Inc.保留所有权利。
As an effective tool to deal with uncertain decision-making, three-way decisions (TWD) have gained wide attention in many applications. Decision-theoretic rough sets (DTRSs) as a classic model of TWD contain two key elements, i.e., conditional probability and loss functions. In this paper, we study the determination of these two elements in depth via the information interaction and modification strategy, and further propose a novel model of TWD. First, fuzzy c-means (FCM) is used to cluster the condition attribute information and loss function information, respectively. Considering the interaction of two types of information, we design the corresponding fusion tactic of these clustering results to get equivalent classes and develop a new calculation method of conditional probability. Then, we use probabilistic hesitant fuzzy sets (P-HFSs) to aggregate the loss functions of different members of the same equivalence class and get the probabilistic hesitant fuzzy elements (P-HFEs) loss functions. In this case, P-HFSs not only reflect the hesitant situation of decision-makers, but also depict the proportion of different opinions. Regarding P-HFEs loss functions, we also investigate the modification methods of its outliers in detail. Moreover, based on the P-HFEs loss functions, we propose TWD with probabilistic hesitant fuzzy decision-theoretic rough sets (P-HFDTRSs). Finally, in order to verify the effectiveness of our proposed method, we develop a series of comparative experiments and discuss the decision results on six UCI datasets. (c) 2021 Elsevier Inc. All rights reserved.