Search Results

In group decision making (GDM), the real or virtual moderator usually provides the suggestion and compensation based on consensus improvement for the decision maker (DM) to promote group consensus. In order to ensure DMs own interests, there are ...

• Explore the relation between subjective trust information and the DM’s consensus.
• Investigates the intrinsic game mechanism and introduces the consensus recognition and trust evolution.
• Constructs the game-driven adjustment model ...

Underwater imaging often suffers from poor quality due to the complex underwater environment and limitations of hardware equipment, leading to images with shallow depth of field and moving objects, which pose a challenge for information fusion of ...

• Enhances underwater image quality and widens view angles.
• Fuses image alignment with seam-driven stitching.
• Refines feature points and eliminates outliers.
• Reduces artifacts by adjusting moving object positions.
• Effective ...

Multimodal fusion for emotion recognition has received increasing attention from researchers because of its ability to effectively leverage multimodal complementary information. However, there are two main challenges lead to performance ...

• Online multi-hypergraph fusion learning method for cross-subject emotion recognition
• Joint of multimodal complementary information and high-order correlations of data
• Hypergraph structure is updating by adding new hyperedges ...

• Self-confidence psychology is considered in behavioral style.
• Optimization method is used to obtain the preference vector.
• A new detection of multiple styles of behavior method is defined.
• Hybrid feedback adjustment mechanism ...

With the rapid increase of experts, groups or organizations involved in decision making, the problem of large-scale group decision making (LSGDM) has attracted increasing attention in the whole research field. Behavioral management and ...

• We propose a joint framework that integrates estimation, consistency improvement and consensus reaching into one phase.
• We propose a minimum adjustment model with completeness, consistency, and consensus control (MAM-CCCC).
• We ...

In group decision making (GDM), there exists a situation in which experts may not able to provide comparative judgements regarding all pairs of alternatives, and therefore leading to the expression of incomplete preference. The existing ...

Multiple Kernel Clustering (MKC) is an effective approach for revealing nonlinear cluster structures in candidate kernels. However, existing MKC methods still face two key challenges. Firstly, the pairwise affinity in these methods is primarily ...

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• A new reconstruction method is developed to explore the local kernel structure.
• A heat diffusion method is developed to exploit the global kernel structure.
• A new sequential MKC method is proposed to explore and exploit kernel ...

Finite mixture such as the Gaussian mixture is a flexible and powerful probabilistic modeling tool for representing the multimodal distribution widely involved in many estimation and learning problems. The core of it is representing the target ...

• Comprehensive analysis and comparison between existing conservative fusion approaches.
• Prove the consistency of the AA density fusion in reducing the MSE under certain conditions.
• Demonstrating how the AA fusion preserves the modes ...

• Propose a semi-supervised classification model for large-scale social network GDM.
• Introduce DMs with missing trust relation to train the classification model.
• Complete the subgroup division under incomplete social relations.
• ...

The fundamental goal of group decision making (GDM) is to improve consensus amongst experts and reduce individual conflicts of interest in the process of alternative selection. By analysing the social network relationships of decision-makers (DMs)...

• An in-depth discussion and analysis of biometric system attacks are provided.
• The prerequisite knowledge required by the adversary to initiate these attacks is given.
• Most recent state-of-the-art protection mechanisms against the ...

It is an undeniable fact that biometric recognition systems are susceptible to different software-related or template attacks at different vulnerable points in the biometric authentication system. However, these attacks are frequently overlooked, ...

• We propose a hospital selection approach.
• Online reviews of general and specialized hospitals are collected and processed.
• We classify topics and sentiments using logistics regression, light GBM, and BERT.
• Preference scores of ...

In the era of big data, publicly available data from official hospital sources and data from online reviews are easy to influence a patient's decision in choosing a hospital. However, existing research has rarely comprehensively considered the ...

Outlier detection aims to find objects that behave differently from the majority of the data. Existing unsupervised approaches often process data with a single scale, which may not capture the multi-scale nature of the data. In this paper, we ...

• A novel information fusion model based on multi-scale fuzzy granules is formulated.
• An unsupervised outlier detection algorithm that integrates multi-scale information is proposed.
• Extensive experiments indicate the effectiveness ...

To group decision-making (GDM) under social network, the interactions are no longer limited to pairwise but can take higher-order interaction, which can affect the consensus process. The higher-order interaction can be represented in simplicial ...

• This paper deeply investigates higher-order interaction-based group consensus model in the simplicial complex.
• We construct the stability of simplex and combine the consensus index to choose the adjustment decision maker.
• The ...

With recent success of deep neural networks, stacked autoencoder networks have received a lot of attention for robust unsupervised representation learning. However, recent autoencoder methods cannot make full use of multi-view information and ...

• Design local and non-local graph constructions for view-specific representations.
• Adapt hierarchical graph structure to stacked autoencoders.
• Propose hierarchical graph augmented stacked autoencoders.

• We propose a maximum fairness consensus approach with individual preventing manipulation consciousness.
• We explore some properties of personalized fairness level.
• We verify the effectiveness of our model by simulation analyses.

Decision makers (DMs) within a social network can communicate and compare with each other on recommendations and compensations received from moderator, which may arise the feelings of being manipulated and unfairness respectively. To prevent ...

• This paper aims to solve multiple criteria sorting problems involving multiple DMs.
• A preference disaggregation approach with uncertain and contradictory preferences.
• Assignment examples and pairwise comparisons for reference ...

Preference disaggregation analysis is effective for inferring a preference model of decision makers from decision examples. Although multiple criteria sorting problems are often handled within the context of group decision-making, it has not been ...

• The FCPNet is proposed to support the fuel loading decisions before flight departure.
• The GCN- and ConvLSTM-based networks are used to consider multi-modal inputs.
• Attention-based fusion is to learn task-oriented features for the ...

Improper fuel loading decision results in carrying excessive dead weight during flight operation, which will burden the airline operation cost and cause extra waste emission. Existing works mainly focused on the post-event fuel consumption based ...

• The multi-criterion decision making supported by machine learning is reviewed.
• We conduct a bibliometric analysis to clarify research status and trends.
• We summarize practical challenges of multi-criterion decision making.
• We ...

Multi-criterion decision making (MCDM) methods can derive alternative rankings as solutions to decision-making problems based on survey or historical data about the performance or preference information of alternatives regarding multiple ...

Multi-view bipartite graph clustering methods select a few representative anchors and then establish a connection with original samples to generate the bipartite graphs for clustering, which maintains impressive performance while reducing time ...

• We observe a significant Cross-view Anchor-level Misalignment (CAM) problem for multiview bipartite graph clustering.
• We transform this tricky CAM problem to an easier cross-view cluster-level anchor alignment problem.
• We propose a ...

Predicting airport arrival flow serves as a crucial technique in air traffic flow management. Given the unique operational characteristics of air traffic systems, airport arrival flow simultaneously presents complex dynamics in spatial–temporal ...

• A full dynamic graph is built based on multiple airport operation concepts.
• A DMGNN block is to capture traffic situation from both local and global views.
• A TAA module is to mine the local trend and global stationarity of traffic ...

Multi-view subspace clustering has aroused more and more attention due to its ability to explore data correlation from multiple views without stressful label annotations. Although a plethora of methods have been developed, they are powerless ...

• We propose multiview clustering model to maintain graph geometry via graph filtering.
• We devise an efficient alternating algorithm to solve the optimization problem.
• Extensive experiments demonstrate the versatility and superiority ...