hasse diagram
- hasse diagram的基本解释
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哈塞图
- 更多网络例句与hasse diagram相关的网络例句 [注:此内容来源于网络,仅供参考]
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Hasse diagram is used to visualize the process, and the algorithm's time complexity can be reduced.
同时,该方法运用Hasse图解进行可视化操作,降低了算法的时间复杂度。
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To solve this problem,this paper presents a new incremental algorithm for building concept lattice based on an ordered set direct product operation,this algorithm is suitable for the case of the insertion of a set of objects into the context,and it can construct the Hasse diagram of the concept lattice while generating the concept.
为了适应这种情况,基于偏序集的直积运算,提出了一种新的增量式概念格构造算法,这种算法可以一次性地加入一个对象集合,而且在生成概念的同时,能够构造出概念格的Hasse图,从而完全解决了上述问题。
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That results in a new class of answer set semantics for ordered logic program including several kinds of already existed semantics. The diverse answer set semantics are compared in detail and a Hasse diagram with respect to set inclusive relations for the semantics is given.
通过证明和举例详细比较了各种回答集语义之间的强弱关系,给出了它们在集合包含关系意义下的哈斯图,证明了各种回答集语义在包含关系下形成格的结构。
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It produces corresponding nonredundent rule by direct generalization of lattice's nodes; This paper also improves the incremental concept formation and Hasse diagram update and apply it to incremental rule generation. We give examples to illustrate the idea of the algorithm and corresponding experimental results. 6 Rough set theory and concept lattice are similar in some aspects, the relationship between them is interesting.
在概念格结构上提出了一种在一定条件下更有效的,在已建造好的概念格上提取规则的算法,这种方法主要依据格结点的直接泛化来产生相应无冗余规则;改进了一种的渐进式更新概念格与相应Hasse图的算法,并将之应用于渐进式规则生成。
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Based on the definition of Boolean function on set and positive extension, The sufficient and necessary condition of PBF is proven. At last, an algorithm of generating MSP expression of stack filter positive Boolean function is presented taking advantage of Hasse diagram.
通过定义布尔函数开、闭集和最小项正、负扩展,证明了布尔函数具有层叠性的充要条件是布尔函数开集的正扩展或闭集的负扩展具有不变性,在此基础上,提出了一种通过Hasse图确定层叠滤波器最简正布尔函数的算法。
- 加载更多网络例句 (2)
- 更多网络解释与hasse diagram相关的网络解释 [注:此内容来源于网络,仅供参考]
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hasse diagram:哈塞图
harmonicity 低性 | hasse diagram 哈塞图 | hausdorff group 豪斯道夫群