火力与指挥控制2026，Vol.51Issue(3)：18-24,7.DOI:10.3969/j.issn.1002-0640.2026.03.003
一种复杂系统评估指标冗余识别和去除方法
An Approach for Identifying and Eliminating Redundant Indicators in Complex System Evaluation
摘要
Abstract
Redundancy in indicator systems is a critical challenge in complex system evaluation.To address the limitations of existing methods that overlook causal mechanisms and rely on redundancy thresholds,a Markov blanket-based approach to indicator reduction is proposed.An optimization objective integrating the minimum redundancy criterion with the maximum information retention criterion is constructed,and both a Markov blanket identification algorithm and a genetic algorithm for indicator reduction are designed to solve the underlying combinatorial optimization problem of redundancy identification and elimination.Experimental results demonstrate the rationality of the proposed method,showing that it achieves a well-balanced trade-off among reduction rate,stability,and interpretability,and yields substantial improvements in redundancy identification accuracy compared with methods such as MIC-MAC and causal entropy.关键词
综合评价/指标体系/指标约简/冗余识别/因果推断Key words
comprehensive evaluation/indicator system/indicator reduction/redundancy identifica-tion/causal inference分类
自科综合引用本文复制引用
林晗,耿梦影,季明,黄其旺,卜先锦..一种复杂系统评估指标冗余识别和去除方法[J].火力与指挥控制,2026,51(3):18-24,7.基金项目
军事类研究生基金资助课题(JY2023C004) （JY2023C004）
