Three-way decisions based multi-attribute decision making with probabilistic dominance relations

Wang, Wenjie; Zhan, Jianming; Zhang, Chao

doi:10.1016/j.ins.2021.01.028

Cited by 70 publications

(21 citation statements)

References 47 publications

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“…In rough set theory, a data or a decision system [35] can be denoted by DS = U, AT, d , in which U is a set of nonempty finite samples, such as U = {x 1 , x 2 , . .…”

Section: Preliminaries 21 Granular Computing and Rough Setmentioning

confidence: 99%

An Ensemble Framework to Forest Optimization Based Reduct Searching

et al. 2022

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Essentially, the solution to an attribute reduction problem can be viewed as a reduct searching process. Currently, among various searching strategies, meta-heuristic searching has received extensive attention. As a new emerging meta-heuristic approach, the forest optimization algorithm (FOA) is introduced to the problem solving of attribute reduction in this study. To further improve the classification performance of selected attributes in reduct, an ensemble framework is also developed: firstly, multiple reducts are obtained by FOA and data perturbation, and the structure of those multiple reducts is symmetrical, which indicates that no order exists among those reducts; secondly, multiple reducts are used to execute voting classification over testing samples. Finally, comprehensive experiments on over 20 UCI datasets clearly validated the effectiveness of our framework: it is not only beneficial to output reducts with superior classification accuracies and classification stabilities but also suitable for data pre-processing with noise. This improvement work we have performed makes the FOA obtain better benefits in the data processing of life, health, medical and other fields.

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“…In rough set theory, a data or a decision system [35] can be denoted by DS = U, AT, d , in which U is a set of nonempty finite samples, such as U = {x 1 , x 2 , . .…”

Section: Preliminaries 21 Granular Computing and Rough Setmentioning

confidence: 99%

An Ensemble Framework to Forest Optimization Based Reduct Searching

et al. 2022

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“… In the current paper, we provide a new calculation method for the state set of conditional probability. In Wang’s method [ 21 ], fixed values of parameters are given subjectively; however, for different decision-makers, the research limits are different, so this method has certain limitations and inflexibility. On the basis of Wang’s method, we set up an adjustable preference parameter k to control the cardinality of the object class, which could help calculate the values of state sets objectively to provide decision-makers with various choices.…”

Section: Introductionmentioning

confidence: 99%

Three-Way Decision Models Based on Ideal Relations in Multi-Attribute Decision-Making

Chen

Zou

2022

Entropy

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In recent years, research on applications of three-way decision (e.g., TWD) has attracted the attention of many scholars. In this paper, we combine TWD with multi-attribute decision-making (MADM). First, we utilize the essential idea of TOPSIS in MADM theory to propose a pair of new ideal relation models based on TWD, namely, the three-way ideal superiority model and the three-way ideal inferiority model. Second, in order to reduce errors caused by the subjectivity of decision-makers, we develop two new methods to calculate the state sets for the two proposed ideal relation models. Third, we employ aggregate relative loss functions to calculate the thresholds of each object, divide all objects into three different territories and sort all objects. Then, we use a concrete example of building appearance selection to verify the rationality and feasibility of our proposed models. Furthermore, we apply comparative analysis, Spearman’s rank correlation analysis and experiment analysis to illustrate the consistency and superiority of our methods.

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“… 2021 ; Wang et al. 2021 ), pattern recognition (Wang and Wang 2009 ), case-based reasoning (Huang and Tseng 2004 ), and data mining (Lingras and Yao 1998 ; Yamaguchi 2009 ).…”

Section: Introductionmentioning

confidence: 99%

Advantage matrix: two novel multi-attribute decision-making methods and their applications

Zhang

2022

Artif Intell Rev

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By comparing attributes of objects in an information system, the advantage matrix on the object set is established in this paper. The contributions can be identified as follows: (1) The advantage degree is proposed by the accumulation of the advantage matrix. (2) Based on the advantage matrix, the advantage (disadvantage) neighborhood approximation operator and the advantage (disadvantage) correlation approximation operator are defined and studied. Based on these two new operators, the neighborhood degree and the correlation degree are presented. The relationships between them are also investigated to demonstrate the value of the proposed method. (3) Finally, based on the above three degrees, new algorithms are designed, in which the effectiveness and robustness of the algorithms are analyzed by practical examples.

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Three-way decisions based multi-attribute decision making with probabilistic dominance relations

Cited by 70 publications

References 47 publications

An Ensemble Framework to Forest Optimization Based Reduct Searching

An Ensemble Framework to Forest Optimization Based Reduct Searching

Three-Way Decision Models Based on Ideal Relations in Multi-Attribute Decision-Making

Advantage matrix: two novel multi-attribute decision-making methods and their applications

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