Ruixia Yan, Jinliang Liu and Bingxue Yao
The purpose of this paper is to present research methods in processing uncertain information.
Abstract
Purpose
The purpose of this paper is to present research methods in processing uncertain information.
Design/methodology/approach
Vague set and rough set are both‐wings‐mode for expressing uncertainty systems, and based on the both‐wings‐mode of expressing uncertainty systems, the connections of vague set and rough set are discussed.
Findings
This paper presents the relationships between vague set and rough set.
Research limitations/implications
Based on these connections between vague set and rough set, theoretical and means of vague set can be used for rough set; also theoretical and means of rough set can be used for vague set.
Originality/value
The paper contributes to the discussion on the research of vague set and rough set. The conclusions are useful in information processing.
Details
Keywords
Jinsong Tu, Yuanzhen Liu, Ming Zhou and Ruixia Li
This paper aims to predict the 28-day compressive strength of recycled thermal insulation concrete more accurately.
Abstract
Purpose
This paper aims to predict the 28-day compressive strength of recycled thermal insulation concrete more accurately.
Design/methodology/approach
The initial weights and thresholds of BP neural network are improved by genetic algorithm on MATLAB 2014 a platform.
Findings
Genetic algorithm–back propagation (GA-BP) neural network is more stable. The generalization performance of the complex is better.
Originality/value
The GA-BP neural network based on the training sample data can better realize the strength prediction of recycled aggregate thermal insulation concrete and reduce the complex orthogonal experimental process. GA-BP neural network is more stable. The generalization performance of the complex is better.
Details
Keywords
Jingda Ding, Ruixia Xie, Chao Liu and Yiqing Yuan
This study distinguishes the academic influence of different papers published in journals of the same subject or field based on the modification of the journal impact factor.
Abstract
Purpose
This study distinguishes the academic influence of different papers published in journals of the same subject or field based on the modification of the journal impact factor.
Design/methodology/approach
Taking SSCI journals in library and information science (LIS) as the research object, the authors first explore the skewness degree of the citation distribution of journal articles. Then, we define the paper citation ratio as the weight of impact factor to modify the journal impact factor for the evaluation of papers, namely the weighted impact factor. The authors further explore the feasibility of the weighted impact factor in evaluating papers.
Findings
The research results show that different types of skewness exist in the citation distribution of journal papers. Particularly, 94% of journal paper citations are highly skewed, while the rest are moderately skewed. The weighted impact factor has a closer correlation with the citation frequency of papers than the journal impact factor. It resolves the issue that the journal impact factor tends to exaggerate the influence of low-cited papers in journals with high impact factors or weaken the influence of high-cited papers in journals with low impact factors.
Originality/value
The weighted impact factor is constructed based on the skewness of the citation distribution of journal articles. It provides a new method to distinguish the academic influence of different papers published in journals of the same subject or field, then avoids the situation that papers published in the same journal having the same academic impact.