Propagating Piecewise-Linear Weights in Temporal Networks
Propagating Piecewise-Linear Weights in Temporal Networks
复制标题
在时态网络中传播分段线性权重
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
Roberto Posenato
中科院分区：
文献类型：
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作者：
Luke Hunsberger;Roberto Posenato
本文提出了一种新的技术，使用分段线性函数（PLF）作为权值的两种时间网络的图中的边缘，以解决一些以前公开的问题。推广约束传播规则以适应PLF权重需要实现少量函数。大多数问题都是通过插入一个或多个初始权重为δ（变量）的边来解决的，然后使用修改后的规则来传播PLF权重。对于一种网络，引入了一组新的传播规则，以避免在传播PLF权重时出现的非终止问题。本文还提出了两个新的结果，以确定最紧的地平线，可以施加，同时保持网络的动态一致性/可控性。
This paper presents a novel technique using piecewise-linear functions (PLFs) as weights on edges in the graphs of two kinds of temporal networks to solve several previously open problems. Generalizing constraint-propagation rules to accommodate PLF weights requires implementing a small handful of functions. Most problems are solved by inserting one or more edges with an initial weight of δ (a variable), then using the modified rules to propagate the PLF weights. For one kind of network, a new set of propagation rules is introduced to avoid a non-termination issue that arises when propagating PLF weights. The paper also presents two new results for determining the tightest horizon that can be imposed while preserving a network’s dynamic consistency/controllability.