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Some cognitive and decision making experiments have demonstrated the classical decision theory may be violated. Recently, the interference effects of quantum theory have attracted a strong interest in applying some fields outside physics. It can be also used to explain the paradox in decision models. Existing some experiments and studies attribute the main reason for the existence of interference effects to uncertain information in decision process. Dempster-Shafer evidence theory extends the framework of discernment to power sets so it can describe unknown and imprecise information. This paper proposes evidential Markov decision-making model based on belief entropy to quantitatively predict and determine the value of interference effects. In new model, the frame of discernment is extended by introducing hesitant or unknown states which could be hidden by participants. Moreover, new model assumes there is no input of any information at initial states so it has the most chaotic states and is determined according to the maximum belief entropy. Finally, this paper discusses the effectiveness of new model by comparing with other methods as studying the interference effects of decision process. [ABSTRACT FROM AUTHOR]

Three-way decision, an essential granular computing research tool, provides an efficient solution to complex and uncertain problems. Behavioral decision theory can analyze the risk preferences of decision-makers effectively. Scholars have conducted preliminary exploration on the fusion of these two theories, but it is still challenging to describe the different types of risk preferences of decision-makers. This paper combines prospect theory with regret theory and studies the compound risk preference modeling of three-way decision to address this issue. Because three attitudes of conflicts coincide with three-way decision, many scholars have conducted multi-dimensional research on three-way conflict analysis and accomplished remarkable results. However, few relevant studies consider psychological factors and risk attitudes of decision-makers, and it is more appropriate to describe agents' attitudes on issues using linguistic terms. This paper applies the proposed three-way decision model based on compounded risk preference and probabilistic linguistic term sets to the conflict analysis problem. We utilize examples to explain the decision-making process of the proposed model and three-way conflict analysis method with the influence of the compounded risk preference under the action of reference point and regret avoidance coefficient. The illustrative example illustrates that the proposed three-way decision model can effectively solve the software development conflict analysis problem for different decision-makers and the comparative analysis shows the advantages of the proposed model and method compared with the two existing methods. Finally, we verify the performance of the three-way decision model based on compounded risk preference by UCI data sets in parameter experiments. The changes of the reference point from 10 to 0 and regret avoidance coefficient in 0, 0.15 and 0.3 respectively demonstrate the trend rule of the model's thresholds and delay-decision rate index. [ABSTRACT FROM AUTHOR]

There has been limited research on considering decision-makers psychological factors and risk attitudes in the early three-way decision theory and methods. Behavioral three-way decision models can better describe and analyze decision-makers risk preferences and behaviors, with prospect theory being prominent. This paper introduces a third-generation prospect theory-based three-way decision model. It characterizes uncertain reference points for decision-maker preferences through positive/negative ideal points and medians. Due to nonlinear weighting functions in prospect theory, closed-form solutions for three-way decision thresholds are absent. The paper introduces α -model and β -model optimizations for numerical threshold solutions, simplifying three-way decision rules. Additionally, the proposed optimized three-way decision model is applied to conflict analysis, considering multi-scale and Z-number information's impact on conflict evaluation. Effective methods for deriving three-way conflict analysis rules and outcomes from multi-scale Z-number information systems are studied. Audit team conflict analysis examples validate the validity and feasibility of the proposed models and methods. Finally, several experimental results with data sets confirm overall performance. [ABSTRACT FROM AUTHOR]

Trackers based on Siamese network have achieved positive performance in recent days. However, most of the existing siamese single object trackers only consider the spatial information in the template which was given in the first frame of the video but do not extract the affluent temporal information. In this paper, we propose a novel tracking framework based on a spatial-temporal network. Specifically, we introduce three-way decision theory into object tracking to avoid interference from complex situations such as occlusions, fast motions, and non-rigid deformation. Furthermore, our proposed method can generate more precise tracking results due to the discriminative correlation filters (DCF). Extensive tests and comparisons with numerous competitive trackers on demanding large-scale benchmarks, including OTB-2015, GOT-10k, LaSOT and VOT2018, TrackingNet, demonstrate that our tracker outperforms many state-of-the-art real-time techniques while operating at 22 frames per second. [ABSTRACT FROM AUTHOR]

Density Peaks Clustering (DPC) is a classic density-based clustering algorithm that has been successfully applied in various areas. However, it assigns samples based on their nearest neighbors with higher density which may lead to an error propagation problem. Besides, it can not detect fringe and overlapping samples. To handle these defects, we improve the density measurement of DPC to make it more adaptive to different shapes and varying densities. Furthermore, we extend DPC to three-way clustering which means a sample in the positive region certainly belongs to the cluster, a sample in the boundary region belongs to the cluster partially and a sample in the negative region certainly does not belong to the cluster. In this paper, we propose a three-way clustering method called TW-RDPC. It mainly consists of three steps: (1) Identify cluster centers and assign other samples based on relative Cauchy kernel density to get initial clusters. (2) Detect potential boundary samples through boundary detection graph. (3) Determine whether potential boundary samples belong to multiple clusters based on the subordinate relationship to their k nearest neighbors. In order to validate TW-RDPC, we compare it to 7 algorithms on 10 synthetic datasets and 8 real-world datasets. Experimental results indicate that TW-RDPC is competitive with the compared 7 algorithms. [ABSTRACT FROM AUTHOR]

Complex evidence theory, as a generation model of the Dempster-Shafer evidence theory, has the ability to express uncertainty and perform uncertainty reasoning. One of the key issues in complex evidence theory is the complex basic belief assignment (CBBA) generation method. But, how to model uncertainty information in complex evidence theory is still an open issue. In this paper, therefore, we propose a CBBA generation method by taking advantage of the triangular fuzzy number. Moreover, an algorithm for decision making is devised based on the proposed CBBA generation method. Finally, the decision making algorithm is applied in classification to verify its effectiveness. In summary, the proposed method can handle uncertainty modeling and reasoning both in the real number domain and the complex number domain, which provides a promising way in decision making theory. [ABSTRACT FROM AUTHOR]

The problem of optimal scale selection for multi-scale decision information systems is an important issue in the field of granular computing research, especially when data are dynamically updated. Determining the changes of the optimal scale for dynamic data is a goal that has drawn increasing attention from scholars in related fields. For the case of object updating, solving this problem requires finding which characteristic conditions should be satisfied by newly added objects when different cases of the optimal scale occur. However, existing studies only include the sufficient and necessary condition of the optimal scale becoming smaller for dynamically updating objects. Therefore, to complete the theory regarding how the optimal scale will be changed when objects are dynamically updated, it is still necessary to explore the sufficient and necessary conditions for the optimal scale being unchanged or becoming larger. In this paper, we use three-way decision theory to study this problem. Concretely speaking, the uncertain region of three-way decision is used to reveal the change of knowledge at different scales. That is, the obtained results, combined with existing work, provide a nice solution to the problem of finding the changing laws of the optimal scale for object updating in multi-scale decision information systems. [ABSTRACT FROM AUTHOR]

The generalized three-way decision (G3WD) theory is featured by a trisecting-acting-outcome paradigm. Experiments in psychology and economics have indicated that risky decision-making problems should take into account the psychological characteristic of agents. Moreover, the loss of information acts as a serious challenge in G3WD. Thus, exploring valid G3WD approaches that consider the mental state of decision-makers in incomplete information systems (IISs) is imperative. This paper explores a new three-way decision (3WD) approach that combines the prospect theory with the regret theory for IISs with the support of fuzzy set pair dominance degrees. First, the notion of fuzzy set pair dominance degrees to process evaluation information in IISs is put forward. Then, an approach that obtains objective reference points and determines the weighting function in the prospect theory is given by combining 3WD with the behavioral decision theory. In light of the prospect theory, a prospect value function is obtained, which is introduced into the regret theory to obtain two utility perception functions. As a consequence, a G3WD approach based on fuzzy set pair dominance degrees and the behavioral decision theory is constructed for IISs. By using two medical cases in the KEEL and UCI datasets, the superiority, effectiveness and stability of the constructed approach are verified via corresponding comparative and experimental analyses. [ABSTRACT FROM AUTHOR]

Label distribution learning (LDL) as a soft-labeling paradigm is allowed to learn single or multi-labeled information distribution. Overwhelmingly, in the open world, the distribution of labels is usually disturbed by the noise (such as the man-made induction bias, shake of hardware devices), which in turn affects the decision of downstream tasks. To address this problem, we propose a novel LDL approach by using the three-way decisions theory to clear the amplified noise in this paper. First, we evaluate the confidence of each training sample and use a three-way decisions-based method to identify the trustworthy samples and the noisy samples. Second, we apply the sample correlation between the trustworthy samples and the noisy samples to correct the noisy labels. Finally, we re-weight every sample based on the learned confidences to train the robust LDL model. Experiments show that our approach has better performance in handling noisy data compared to existing algorithms. [ABSTRACT FROM AUTHOR]

In group decision making (GDM) of organization management, information interaction usually occurs via the hierarchical social networks. In the hierarchical social networks, the relation and opinion exchange between decision makers and participants can influence the consensus reaching of three-way group decision. In this paper, we deeply explore the three-way group decision consensus reaching by constructing adjustment mechanism based on the hierarchical social networks. In the hierarchical social network, we firstly learn the attitudes of participants for the opinions of decision makers. Inspired by the thought of three-way decision, we successfully identify the valid followers, hesitant followers and invalid follower of decision makers from the participants with the aid of the trust and consensus information. According to the character of followers, we compute the real influence of decision makers. Then, we discuss the consensus model. In the adjustment process of GDM of social network, the inconsistent decision makers tend to adjust evaluation based on the evaluation of the most influential decision makers. Thus, we introduce the maximum closeness degree between the inconsistent decision maker and the most influential decision maker to construct the minimum adjustment consensus model. Besides, we extend the minimum adjustment consensus model by considering the various unit cost and limited adjustment budget. In light of the consensual loss information and Bayesian decision theory, we determine the classification rules of three-way group decision. Finally, we use an example of the medical equipment selection of purchasing department to elaborate and validate our proposed method. [ABSTRACT FROM AUTHOR]

Conflict occurs naturally in all walks of life at any time. When agents face a conflict, they usually have multiple alternatives and hesitate to make a decision. This paper studies conflict analysis in the case of hesitant fuzzy setting, i.e. the attitude of an agent on an issue has multiple choices. We first propose a conflict analysis model based on hesitant fuzzy information systems. Subsequently, we present the concepts of conflict, neutrality and alliance sets on one issue and multiple issues respectively, and introduce a method to compute the three sets via Bayesian decision theory. Moreover, the degree of conflict, neutrality and alliance among agents with respect to an issue are defined respectively. According to the conflict and alliance degrees, the set of issues is divided into three parts: the main reason, secondary reason and irrelevant reason. Finally, two methods of computing coalitions are discussed. One is based on Bayesian decision theory. The other is to find a complete subgraph of the coalition graph. [ABSTRACT FROM AUTHOR]

A recent study conducted by researchers at Sichuan University in Chengdu, China explores the use of computer algorithms to mimic the route choices made by human players in wargames. The researchers developed a fuzzy dynamic route choice model and algorithm that takes into account the uncertain and dynamic decision-making environment of wargaming. The model was applied to a practical case and demonstrated its effectiveness in handling fuzzy and uncertain information while simulating the decision-making psychology of wargame players. This research provides a new method for automatic route choice in wargame simulations. [Extracted from the article]

Three-way decision theory (3WD) provides a reasonable solution to solve multi-criteria decision-making (MCDM) problems and reduces more decision risks than two-way decision (2WD). However, the impact of preferences on decision results has not been reasonably considered in 3WD. Thus, this paper proposes a preference-based regret 3WD model on multiple decision information systems (MDISs) with linguistic Z-numbers (LZNs) to address the defect. First of all, a Z-LINMAP method is proposed by extending LINMAP method into the LZNs environment to derive criteria weights, Z-number ideal solutions and preference coefficients. On the basis of preference coefficients, the consistency-order and inconsistency-order are defined and further the consistency and inconsistency equivalence classes are presented to derive the conditional probabilities of alternatives. Then, the regret loss functions based on regret theory are presented and the regret 3WD rules of a single decision information system are designed. Furthermore, the weighted expected regret loss function and loss score function are defined to classify and rank all alternatives for MDISs. Finally, the proposed 3WD model is applied to the image recognition case with human-computer interaction to verify the effectiveness, and the comparative and sensitivity analyses are carried out to demonstrate the feasibility of our model. • A Z-LINMAP method to measure the reliability of decision information is proposed. • The consistency-order and inconsistency-order based on preferences are defined. • Two new equivalence classes are proposed to derive the conditional probability. • Regret loss functions and the preference-based regret 3WD rules are presented. • It can effectively classify and rank alternatives for MDISs. [ABSTRACT FROM AUTHOR]

• The study proposes a decision matrix for SSL frameworks, which are 37 SSL alternatives and 19 assessment criteria. • This paper focuses on the prioritisation of factors of SSL frameworks based on C-PFS-FWZIC. • This study develops TWD-based MCDM to rank and grade SSL frameworks using C-PFS-CPOS and C-PFVs. Sustainable smart living (SSL) is a crucial component in the emergence of smart cities. These cities offer potential solutions to address pressing urban challenges, including traffic congestion, energy consumption and environmental degradation. Recently, many SSL frameworks have been developed based on multiple factors. However, no framework can simultaneously address all these factors. Furthermore, no research has ranked and graded the identified SSL frameworks to select the most sustainable framework. These are considered challenging tasks. To address these challenges, three-way decisions (TWD) and multicriteria decision-making (MCDM) can serve as a valuable solution for city planners and decision-makers. This study introduces TWD-based MCDM as novel conditional probabilities by opinion scores (CPOS) within the context of circular-Pythagorean fuzzy sets (C-PFSs), namely, C-PFSs-CPOS method, to estimate the conditional probability of each alternative. Additionally, Bayesian decision theory within a C-PFS environment is employed to construct the decision thresholds for each alternative. Furthermore, the prioritisation of factors that impact the ranking and grading of SSL frameworks is achieved through the application of the fuzzy-weighted zero-inconsistency (FWZIC) method within a C-PFS environment, namely, C-PFS-FWZIC method. A total of 37 SSL frameworks (alternatives) are evaluated on the basis of 19 assessment factors (criteria) distributed in 4 layers. Results show that six alternatives exhibit a high level of sustainability, as evidenced by their position in the positive region, whereas two alternatives consistently fall within the negative region for all σ values. At σ = 0.05 , the remaining SSL framework alternatives are positioned within the boundary region. When σ value increases to a range of 0.55–0.59, TWD is transformed into a two-way decision-making. Sensitivity and correlation analyses are conducted to evaluate the stability and robustness of the proposed methods. [ABSTRACT FROM AUTHOR]

Group decision-making is an important branch of decision-making theory. And comprehensive ranking is an important branch of group decision-making theory. The Borda rule and Copeland rule are common ranking methods in group decision-making. This paper demonstrates that the ranked outputs of these two methods are unreasonable and cannot accurately reflect the inner structure of the ranked inputs in some cases. In order to objectively quantify the difference between two rankings, the concept of the relative inverse number (RIN) is proposed. Then a ranking rule, also called the voting rule, based on RIN is proposed. The RIN rule analyzes the structure of the ranked inputs more comprehensively than the Borda rule and the Copeland rule, and the output of the RIN rule is more precise in the sense that the alternative with more votes from the individuals is always ranked ahead in the RIN rule while may be ranked behind in other rules. However, the complexity of the RIN rule increases exponentially with the number of alternatives. Fortunately, combined with the Borda rule or other existing ranking rules, a fast solution algorithm to search the RIN rule output has been designed. In the applications of the RIN rule in science and technology evaluation, computational complexity is reduced by 105 to 1021 times utilizing the proposed algorithm. [ABSTRACT FROM AUTHOR]

Purpose: In the era of information overload, the density of tourism information and the increasingly sophisticated information needs of consumers have created information confusion for tourists and scenic-area managers. The study aims to help scenic-area managers determine the strengths and weaknesses in the development process of scenic areas and to solve the practical problem of tourists' difficulty in quickly and accurately obtaining the destination image of a scenic area and finding a scenic area that meets their needs. Design/methodology/approach: The study uses a variety of machine learning methods, namely, the latent Dirichlet allocation (LDA) theme extraction model, term frequency-inverse document frequency (TF-IDF) weighting method and sentiment analysis. This work also incorporates probabilistic hesitant fuzzy algorithm (PHFA) in multi-attribute decision-making to form an enhanced tourism destination image mining and analysis model based on visitor expression information. The model is intended to help managers and visitors identify the strengths and weaknesses in the development of scenic areas. Jiuzhaigou is used as an example for empirical analysis. Findings: In the study, a complete model for the mining analysis of tourism destination image was constructed, and 24,222 online reviews on Jiuzhaigou, China were analyzed in text. The results revealed a total of 10 attributes and 100 attribute elements. From the identified attributes, three negative attributes were identified, namely, crowdedness, tourism cost and accommodation environment. The study provides suggestions for tourists to select attractions and offers recommendations and improvement measures for Jiuzhaigou in terms of crowd control and post-disaster reconstruction. Originality/value: Previous research in this area has used small sample data for qualitative analysis. Thus, the current study fills this gap in the literature by proposing a machine learning method that incorporates PHFA through the combination of the ideas of management and multi-attribute decision theory. In addition, the study considers visitors' emotions and thematic preferences from the perspective of their expressed information, based on which the tourism destination image is analyzed. Optimization strategies are provided to help managers of scenic spots in their decision-making. [ABSTRACT FROM AUTHOR]

A new report from the London School of Economics and Political Science discusses the concept of utilitarianism in philosophy. Utilitarianism is the belief that one should choose the option that maximizes overall well-being. However, utilitarianism is not widely accepted among moral philosophers due to the "Integrity Objection" proposed by Williams in 1973. This objection argues that agents who accept utilitarianism cannot be psychologically committed to their own projects. The research explores different interpretations of the objection and concludes that the psychological problem it presents is difficult for utilitarians to avoid. The study has been peer-reviewed and more information can be found in the journal article. [Extracted from the article]

Keywords: Elderly Care; Health and Medicine; Mathematics EN Elderly Care Health and Medicine Mathematics 4870 4870 1 08/07/23 20230811 NES 230811 2023 AUG 11 (NewsRx) -- By a News Reporter-Staff News Editor at Health & Medicine Week -- New study results on mathematics have been published. Finally, the proposed method is applied to the case of performance evaluation of elderly-care services to demonstrate the effectiveness of the method, and comparative analyses are given to verify the superiority of the proposed method.". [Extracted from the article]

Keywords for this news article include: Aalborg University, Viral, COVID-19, Virology, SARS-CoV-2, RNA Viruses, Severe Acute Respiratory Syndrome Coronavirus 2. Keywords: COVID-19; Coronavirus; RNA Viruses; SARS-CoV-2; Severe Acute Respiratory Syndrome Coronavirus 2; Viral; Virology EN COVID-19 Coronavirus RNA Viruses SARS-CoV-2 Severe Acute Respiratory Syndrome Coronavirus 2 Viral Virology 2023 MAR 5 (NewsRx) -- By a News Reporter-Staff News Editor at NewsRx COVID-19 Weekly -- New research on COVID-19 is the subject of a new report. COVID-19, Coronavirus, RNA Viruses, SARS-CoV-2, Severe Acute Respiratory Syndrome Coronavirus 2, Viral, Virology. [Extracted from the article]