激活扩散模型是 分层网络模型 ( Hierarchical Network Models ) (Collins &Quillian, 1969; 1970)的改进版。分层网络模 型是针对言语理解的计算机模拟而提出的。
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Therefore, the negative effects are the powerful supportive verification for hierarchical network models of memory.
因此，否定效应是支持记忆的层次网络模型的有力证据。
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.
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。
This model is normally more difficult for programmers to work with and is harder to maintain than the hierarchical and network models.
这种模式一般是比较难的程序员一起工作，是难以维持较层次和网络模型。
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