Peide Liu
Biographic Data
| ID | 9439599 |
|---|---|
| NAME | Peide Liu |
| GIVEN NAMES | Peide |
| FAMILY NAME | Liu |
| SIGNATURE | LIU P |
| AFFILIATIONS | Shandong University of Finance and Economics |
| ORCID | 0000-0002-2184-3520 |
| VERIFIED | Yes |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 6 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
A Novel Group Decision-Making Method Considering Bounded Confidence and Non-cooperative Behaviors Under Incomplete Information
A Community Structure-Based GMCR Framework for Power-Asymmetric Conflict Resolution Under Linguistic Distribution Information
Tourist attraction recommendation using a multi-dimensional QFD-based cumulative prospect theory method with probabilistic linguistic information
The exponential increase of tourist attractions (TAs) produces ‘information overload’, which causes tourists to choose too much and have no choice. Therefore, one of the most critical issues in tourism is recommending a prefect TA for tourists from among the candidate ones. However, most of the existing studies on TA recommendation fail to notice tourists’ need classification, different risk preferences and the influence of extreme preference val…
A Linguistic Cloud-Based Consensus Framework with Three Behavior Classifications Under Trust-Interest Relations
Temporal-spatial evolution of green total factor productivity in China's coastal cities under carbon emission constraints
Big Data and Intelligent Decisions
No prominent works on this page.
Big Data and Intelligent Decisions
Temporal-spatial evolution of green total factor productivity in China's coastal cities under carbon emission constraints
A Linguistic Cloud-Based Consensus Framework with Three Behavior Classifications Under Trust-Interest Relations
Tourist attraction recommendation using a multi-dimensional QFD-based cumulative prospect theory method with probabilistic linguistic information
The exponential increase of tourist attractions (TAs) produces ‘information overload’, which causes tourists to choose too much and have no choice. Therefore, one of the most critical issues in tourism is recommending a prefect TA for tourists from among the candidate ones. However, most of the existing studies on TA recommendation fail to notice tourists’ need classification, different risk preferences and the influence of extreme preference val…
A Novel Group Decision-Making Method Considering Bounded Confidence and Non-cooperative Behaviors Under Incomplete Information
A Community Structure-Based GMCR Framework for Power-Asymmetric Conflict Resolution Under Linguistic Distribution Information
Multi-Criteria Decision Making (4 works) · Computer Science (3 works) · Cognitive Science and Mapping (2 works) · Management science (2 works) · Mathematics (2 works) · Preference (2 works) · Probabilistic logic (2 works) · Attraction (1 work) · Bayesian Modeling and Causal Inference (1 work) · Big data (1 work)