Witold Pedrycz
Biographic Data
| ID | 255332 |
|---|---|
| NAME | Witold Pedrycz |
| GIVEN NAMES | Witold |
| FAMILY NAME | Pedrycz |
| SIGNATURE | PEDRYCZ W |
| AFFILIATIONS | University of Alberta |
| ORCID | 0000-0002-9335-9930 |
| VERIFIED | Yes |
| TOTAL WORKS | 19 |
| TOTAL CITATIONS | 1 |
| AUTHOR COUNT | 18 |
| EDITOR COUNT | 1 |
| FIRST PUBLICATION YEAR | 1983 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 1 |
Overlapping Community Detection to Generate a Maximum Proximity-Driven Feedback Method for Group Consensus Under Social Network
With the rise of social network group decision-making (SN-GDM), research on trust relationships has aided in achieving group consensus. However, as network structures grow more complex, there is a growing focus on studying overlapping communities. Most existing methods do not take into account the overlap between communities, thereby not fully revealing the interactive consensus within groups where many users are involved. Additionally, the role …
Physics-Informed Neural Network With Adaptive Clustering Learning Mechanism for Information Popularity Prediction
With society entering the Internet era, the volume and speed of data and information have been increasing. Predicting the popularity of information cascades can help with high-value information delivery and public opinion monitoring on the internet platforms. The current state-of-the-art models for predicting information popularity utilize deep learning methods such as graph convolutional networks (GCNs) and recurrent neural networks (RNNs) to ca…
A Stitch in Time Saves Nine: Progressive Information Bottleneck for Incremental Multiview Clustering
Incremental multiview clustering (IMVC) leverages consistent information between historical and new views to benefit the clustering task. However, existing IMVC approaches ignore the redundant information in individual views, leading to an accumulation of irrelevance. Besides, with the continuous arrivals of new views, the knowledge learned from historical views is often forgotten, which hinders the learning models from achieving long-term depend…
An Information Diffusion-Based Consensus Model for Large-Scale Group Decision-Making in a Social Network Environment
A Dual-Level Bio-Inspired Optimization Algorithm for Cloud Manufacturing Service Evaluation on Industrial Internet of Things (IIoT) Platforms
Inspired by the immune-endocrine system, an improved biological comprehensive optimization algorithm (IBCOA) is proposed for industrial big data analysis and cloud manufacturing service matching. IBCOA employs a dual-level strategy: a bottom-level global optimization immune algorithm (GOIA) narrows down the search space to optimize short-term parameters, while a top-level fuzzy weighted comprehensive evaluation (FWCE) refines the solutions by inc…
Skeleton-Based Action Recognition Using Multibranch Adaptive Graph Convolutional Network With Pose Refinement
A multibranch adaptive graph convolutional network is proposed for human action recognition by combining graph convolutional networks (GCNs), adaptive learning, and multibranch feature extraction. Through the adaptive graph convolution module, this method can adaptively change parameters during the training process, thereby enhancing the flexibility of the model. Furthermore, the integration of shallow-level features (skeleton joints), with deep-…
Supply Chain Conflict Study Based on Graph Model with a New Integrated Preference Structure
ScamGen: Unveiling psychological patterns in tele-scam through advanced template-augmented corpus generation
Fuzzy Inference System for Measuring Composite Indicators' Overall Quality
Concept Design Evaluation of Sustainable Product–Service Systems: A QFD–Topsis Integrated Framework with Basic Uncertain Linguistic Information
Machine learning in human creativity: Status and perspectives
Machine Learning in Society: Prospects, Risks, and Benefits
Towards a mixed human-machine creativity
Ranking Objects from Individual Linguistic Dual Hesitant Fuzzy Information in View of Optimal Model-Based Consistency and Consensus Iteration Algorithm
Assessing alternatives of including social robots in urban transport using fuzzy trigonometric operators based decision-making model
Current trends point to a not-too-distant future with qualitatively advanced interactions between humans and social robots. It is critical to consider the possibility of forming meaningful social relationships with robots when defining the future of human-robot interactions, as well as studying how these interactions will evolve to the point where humans are unable to distinguish between humans and robots in urban transportation. In this study, t…
Fuzzy Analytic Hierarchy Process in a Graphical Approach
Handbook of Granular Computing
Fuzzy Systems Engineering: Toward Human‐Centric Computing
A fuzzy extension of Saaty's priority theory
A fuzzy extension of Saaty's priority theory
Fuzzy Systems Engineering: Toward Human‐Centric Computing
Handbook of Granular Computing
Fuzzy Analytic Hierarchy Process in a Graphical Approach
Ranking Objects from Individual Linguistic Dual Hesitant Fuzzy Information in View of Optimal Model-Based Consistency and Consensus Iteration Algorithm
Assessing alternatives of including social robots in urban transport using fuzzy trigonometric operators based decision-making model
Current trends point to a not-too-distant future with qualitatively advanced interactions between humans and social robots. It is critical to consider the possibility of forming meaningful social relationships with robots when defining the future of human-robot interactions, as well as studying how these interactions will evolve to the point where humans are unable to distinguish between humans and robots in urban transportation. In this study, t…
Concept Design Evaluation of Sustainable Product–Service Systems: A QFD–Topsis Integrated Framework with Basic Uncertain Linguistic Information
Machine learning in human creativity: Status and perspectives
Machine Learning in Society: Prospects, Risks, and Benefits
Towards a mixed human-machine creativity
A Dual-Level Bio-Inspired Optimization Algorithm for Cloud Manufacturing Service Evaluation on Industrial Internet of Things (IIoT) Platforms
Inspired by the immune-endocrine system, an improved biological comprehensive optimization algorithm (IBCOA) is proposed for industrial big data analysis and cloud manufacturing service matching. IBCOA employs a dual-level strategy: a bottom-level global optimization immune algorithm (GOIA) narrows down the search space to optimize short-term parameters, while a top-level fuzzy weighted comprehensive evaluation (FWCE) refines the solutions by inc…
Skeleton-Based Action Recognition Using Multibranch Adaptive Graph Convolutional Network With Pose Refinement
A multibranch adaptive graph convolutional network is proposed for human action recognition by combining graph convolutional networks (GCNs), adaptive learning, and multibranch feature extraction. Through the adaptive graph convolution module, this method can adaptively change parameters during the training process, thereby enhancing the flexibility of the model. Furthermore, the integration of shallow-level features (skeleton joints), with deep-…
Supply Chain Conflict Study Based on Graph Model with a New Integrated Preference Structure
ScamGen: Unveiling psychological patterns in tele-scam through advanced template-augmented corpus generation
Fuzzy Inference System for Measuring Composite Indicators' Overall Quality
Overlapping Community Detection to Generate a Maximum Proximity-Driven Feedback Method for Group Consensus Under Social Network
With the rise of social network group decision-making (SN-GDM), research on trust relationships has aided in achieving group consensus. However, as network structures grow more complex, there is a growing focus on studying overlapping communities. Most existing methods do not take into account the overlap between communities, thereby not fully revealing the interactive consensus within groups where many users are involved. Additionally, the role …
Physics-Informed Neural Network With Adaptive Clustering Learning Mechanism for Information Popularity Prediction
With society entering the Internet era, the volume and speed of data and information have been increasing. Predicting the popularity of information cascades can help with high-value information delivery and public opinion monitoring on the internet platforms. The current state-of-the-art models for predicting information popularity utilize deep learning methods such as graph convolutional networks (GCNs) and recurrent neural networks (RNNs) to ca…
A Stitch in Time Saves Nine: Progressive Information Bottleneck for Incremental Multiview Clustering
Incremental multiview clustering (IMVC) leverages consistent information between historical and new views to benefit the clustering task. However, existing IMVC approaches ignore the redundant information in individual views, leading to an accumulation of irrelevance. Besides, with the continuous arrivals of new views, the knowledge learned from historical views is often forgotten, which hinders the learning models from achieving long-term depend…
An Information Diffusion-Based Consensus Model for Large-Scale Group Decision-Making in a Social Network Environment
Computer Science (13 works) · Artificial Intelligence (8 works) · Mathematics (8 works) · Multi-Criteria Decision Making (6 works) · Psychology (5 works) · Fuzzy logic (4 works) · Operations research (4 works) · Business (3 works) · Complex Network Analysis Techniques (3 works) · Data mining (3 works)