层次网络模型是概念结构理论的一种,除此之外较为公认的还有里伯的内隐学习理论,Bourne等人的特征表理论和Rosch的原型模型
这为隐喻的语义表征的层次网络模型提供了证据。
This provides supporting evidence for the hierarchical network model of semantic representation of metaphors.
因此,否定效应是支持记忆的层次网络模型的有力证据。
Therefore, the negative effects are the powerful supportive verification for hierarchical network models of memory.
但是现有的层次网络模型和最优路径算法难以扩展到时变、随机网路中,为此本文提出了网络树模型和最优路径算法。
But it is difficulty to expand the existing hierarchical network models and algorithms for finding optimal path problems in the stochastic and time-dependent network.
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