Cascading failures can easily occur and cause a major blackout in power grid when an important node breaks down. It is an essential problem to evaluate the importance of nodes in power system planning and operation. I...
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Cascading failures can easily occur and cause a major blackout in power grid when an important node breaks down. It is an essential problem to evaluate the importance of nodes in power system planning and operation. In this study, a method for evaluating the importance of power grid nodes based on PageRank (pr) algorithm is proposed. First, according to the comparison of the internet and power grid topology, a directed graph is established. Second, based on the directed graph, an index is proposed to estimate the importance of power grid nodes based on pr algorithm. Then, according to the characteristics of power grid, a modified algorithm, which takes the importance of nodal load, nodal load capacity and network topology into account, is proposed. Finally, case study shows the necessity of considering the factors to evaluate the importance of power grid nodes and the effective of index and algorithm to identify critical nodes in this study.
In recent years, with the development of various knowledge bases, the fusion of multi-source knowledge bases is a hot and difficult problem facing the field of knowledge fusion. Due to the large differences in knowled...
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ISBN:
(纸本)9781728181561
In recent years, with the development of various knowledge bases, the fusion of multi-source knowledge bases is a hot and difficult problem facing the field of knowledge fusion. Due to the large differences in knowledge base structure, the efficiency and accuracy of fusion are not high. proposed Graph Structure Fusion, a totally new knowledge fusion method based on pr(PageRank) algorithm and feature selection. This method constructs a network graph for entity content. The pr value of each node is used to determine the closeness of the relationship with the target word, and the pr value is used to select Relevant entities, excluding irrelevant entities to improve computing efficiency, and then from the perspective of graph structure, fusion of multi-source knowledge base. Experiments show that the average precision of the algorithm is 92.8%.
Computers are very systemized and none of the procedures conducted by them are random. But computers are seldom required to generate a random number for many practical applications like gaming, accounting, encryption/...
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ISBN:
(数字)9789811075636
ISBN:
(纸本)9789811075636;9789811075629
Computers are very systemized and none of the procedures conducted by them are random. But computers are seldom required to generate a random number for many practical applications like gaming, accounting, encryption/decryption and many more. The number generated by the computer relies on the time or the CPU clock. A given computer can be programmed to return random number (or character) arrays from a number (or character) data set. The returned dataset can have repeated values. Even though the repeated values are not related with its degree of randomness (in fact, it may be a sign of higher randomization), but still to humans, it appears as biased or not random. We propose an algorithm to minimize repetition of values in the returned data set so as to make it appear more random. The concept proposes returning a data set by using biased or nonrandom procedure in order to make it more random in "appearance".
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