.png){kind=icon}
返回
A Quick Algorithm to Determine 2-Optimality Consensus for Collectives
.png){kind=icon}
OA
AI
DOI：10.1109/ACCESS.2020.3043371.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Nowadays, to solve a problem, people/systems typically use knowledge from different sources. A binary vector is a useful structure to represent knowledge states, and determining the consensus for a binary vector collective is helpful in many areas. However, determining a consensus that satisfies postulate 2-Optimality is an NP-hard problem; therefore, many heuristic algorithms have been proposed. The basic heuristic algorithm is the fastest in the literature, and most widely used to solve this problem. The computational complexity of the basic heuristic algorithm is O(m(2)n). In this study, we propose a quick algorithm (called QADC) to determine the 2-Optimality consensus. The QADC algorithm is developed based on a new approach for calculating the distances from a candidate consensus to the collective members. The computational complexity of the QADC algorithm has been reduced to O(mn), and the consensus quality of QADC algorithm and the basic heuristic algorithm is the same.
Keyword:
Heuristic algorithms
Prediction algorithms
Diseases
Proteins
Partitioning algorithms
Uncertainty
Time complexity
Collective intelligence
collective knowledge
consensus
heuristic algorithm
2-optimality consensus
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
机构
引用论文
分享收藏Application of Internet of Things and Blockchain Technologies to Improve Accounting Information Quality.png)
IEEE ACCESSOAAI
IEEE ACCESSIF3.6
OAAI分享收藏分享收藏
查看更多内容