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语言结构词性流量的冲量过程 被引量:3

The Pulse Process Model of Rate of Natural Language Lexical Category Flow
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摘要 基于最大语言结构信息熵构想,运用随机抽取的219份样本进行检验,计算出实际样本最理想语言结构信息熵,建构语言结构冲量过程模型,得到语言结构冲量过程稳定性诊断原则,并对6个不稳定样本进行训练与改进。在实际的心理状态诊断和干预中,通过改变语言结构系统中的向量脉冲量,可以促使个体的心理状态发生变化,从而帮助个体适应变化的情境。 Base on the conception of maximum natural language structural information entropy and 219 sample date sets, we figured out the reality structural information entropy. We discovered the language structure pulse process model and got diagnosis principles about pulse process stability. 6 unstable samples were found and trained to improvement. In the practical application of to diagnose and intervene individuality mental state, we may change the vector pulse to impel some variety of personality state, which would help people to adapt metabolic circumstance.
出处 《数理统计与管理》 CSSCI 北大核心 2013年第4期685-698,共14页 Journal of Applied Statistics and Management
基金 教育部人文社会科学研究规划项目(11YJAZH106)
关键词 语言结构 词性流量 冲量过程 language structure, rate of lexical category flow, pulse process
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参考文献19

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二级参考文献52

共引文献20

同被引文献31

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