1) inference tree methods
推理树法
2) tree inference
树推理
1.
This paper, based on the simple tree inference structure, has developed therelationship between some of the formulas.
本文通过对概率逻辑推理树知识结构模型的研究，得出在树推理中对矩阵列消减起主要作用的相邻关系及其计算方法，给出了树推理模型的有效赋值列数的一般计算方法。
3) cluster tree inference
簇树推理
4) reasoning tree structure
推理树结构
1.
According to the course of the forward reasoning and extremely little frequency update for the knowledge-base of the expert system, a kind of new reasoning tree structure based on production rule is proposed, which adopts hierarchy and classification in rule storing and greatly accelerates the reasoning of the reasoning machine.
根据正向推理机推理的过程,以及专家系统知识库更新频率极小的特点,描述了一种新的基于产生式规则的推理树结构,这种树结构采用分层分类别的存储方法,大大提高了推理机推理效率。
5) goal-tree deduce
目标树推理
6) Reasoning algorithm
推理算法
1.
New reasoning algorithm based on EFALC;
一个新的基于EFALC的推理算法(英文)
2.
It gives the models and concerned concepts of extension reasoning,and discusses realizing process of reasoning algorithm.
根据可拓学理论，给出了可拓推理模型和可拓推理的有关概念，并讨论了推理算法的实现过程。
3.
Weighted Fuzzy Petri Net is combined with matrix operations,and a reasoning algorithm is proposed to achieve the reasoning of knowledge.
将加权模糊Petri网与矩阵运算相结合,提出了一种推理算法,实现知识的推理运用。
补充资料：演绎推理(见推理)
演绎推理(见推理)
deductive inference
住理。yanyl tullj演绎推理(deduetive infer。二ee)见
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条