Evidence map›Paper›PMID 40222969›Full record

ArticleScientific reports2025

An effectiveness assessment ensemble for transmission corridor mechanized construction schemes based on weighted itemset mining and factor criticality analysis.

Xin Yang, Junyao Hu, Chenhao Sun, Yafei Huang, Ci Tang, Jie Huang

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In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Xin YangSchool of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha, 410114, China.
Junyao HuSchool of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha, 410114, China.
Chenhao SunSchool of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha, 410114, China. chenhaosun@csust.edu.cn.
Yafei HuangSchool of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha, 410114, China.
Ci TangSchool of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha, 410114, China.
Jie HuangSchool of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha, 410114, China.

Funding

Natural Science Foundation of Changsha kq2208231Natural Science Foundation of China 52177015Natural Science Foundation of China 52207074Natural Science Foundation of Hunan 2024JJ9175Natural Science Foundation of Hunan 2024JJ9182
6 · The paper itself

Abstract

A reasonable assessment of overall effective levels, incorporating dimensions such as risks, durations, and costs, will be salutary for the rational planning and better selection of optional transmission corridor mechanized construction schemes. With this motivation, this paper establishes an ensemble to address the issue of effective level diagnoses, and thus the hidden patterns and regularities between scheme features and effective levels can be explored. Based on the complex characteristics of input data, the Pearson correlation coefficient is deployed to handle the multidimensional data from multiple sources, and K-means clustering is then employed to classify scheme indicators into classes. The Weighted Itemset Mining (W-IM) model is proposed to identify the underlying key factors, to cope with the frequent omission of High Impact Low Probability (HILP) factors during the qualitative analysis stage. Next, the Factor Criticality Analysis (FCA) model is built to quantify the specific impact levels of these distinguished key elements. Finally, the significance proportion of individual features to the overall effectiveness can be determined and optimized according to the Entropy Impact Model (EIM) model. An empirical case study indicates that the proposed ensemble in this paper exhibits higher predictive accuracy along with better flexibility and comprehensiveness.

Indexed as

Entropy impact methodEvaluation of mechanized construction schemesItem mining algorithmPearson coefficientWeight optimization

Identifiers

PMID40222969
PMCPMC11994785

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