A posterior double threshold power Apriori parallel method based on Boolean matrix

A Boolean matrix, double-threshold technology, applied in the field of electric power, can solve the problems of less research on the Apriori algorithm of electric power big data, the simplicity of the algorithm data is not good enough, and the accuracy of the algorithm is reduced, so as to ensure the same importance and reduce the number of scans and calculations. , to ensure the effect of efficiency and simplicity

Inactive Publication Date: 2019-03-12
TIANJIN UNIV OF SCI & TECH +2
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Problems solved by technology

[0007] However, although this method has achieved remarkable results in some research aspects, the algorithm data is not concise enough, which may produce a large number of frequent candidate sets, resulting in inaccurate output results and reducing the accuracy of the algorithm.
[0008] In addition, at present, there are few studies on frequent itemset mining algorithms for power big data, so there are relatively few studies on the Apriori algorithm based on Boolean matrix posterior double threshold posterior double threshold power big data

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  • A posterior double threshold power Apriori parallel method based on Boolean matrix
  • A posterior double threshold power Apriori parallel method based on Boolean matrix
  • A posterior double threshold power Apriori parallel method based on Boolean matrix

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[0055] The present invention is further described below in conjunction with the examples; the following examples are illustrative, not restrictive, and the protection scope of the present invention cannot be limited by the following examples.

[0056] The devices used in the present invention are commonly used in the field unless otherwise specified; the methods used in the present invention are commonly used in the field unless otherwise specified.

[0057] An Apriori parallel method for a posteriori dual-threshold power big data based on a Boolean matrix, the method comprises the following steps:

[0058] The present invention optimizes and improves each link of the Apriori algorithm, such as figure 1 shown. In the data processing stage, the Boolean matrix is ​​used to compress the transaction matrix and reduce the number of computations, so as to improve the computational efficiency of the algorithm. In the data reading stage, the concept of removal rate is introduced, an...

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Abstract

The invention relates to a posterior double-threshold electric power big data Apriori parallel method based on Boolean matrix. The method comprises the following steps: step 1, data are compressed byBoolean matrix; step 2, removal rate is introduced for pruning; step 3, double-threshold parallel processing is performed; Step 4: the result is verified using the lifting degree. A posterior double-threshold Apriori parallel algorithm is adopted in this method, and the concepts of Boolean matrix and removal rate are introduced to prune and compress the data, Realize the algorithm and apply it tothe electric power big data, achieve the purpose of reducing the number of calculation, ultimately realize the electric power big data efficient parallel calculation, effectively solve the calculationbottleneck problem of the electric power big data, effectively improve the accuracy, efficiency and quantity of the electric power big data.

Description

technical field [0001] The invention belongs to the field of electric power technology, in particular to a Boolean matrix-based posterior double-threshold electric power big data Apriori parallel method. Background technique [0002] With the development of economy and technology, the power system has become an important foundation for social development. Mastering the key technologies of power big data application will be beneficial to the sustainable development of the power industry and the establishment of a strong smart grid. After years of development and precipitation, State Grid has accumulated a considerable amount of customer file data and massive power supply service information across the entire network, as well as company marketing, power grid production and other data. Therefore, how to quickly calculate and analyze the massive power grid business data provides a reference for the rapid construction of smart grids, and has important research significance for th...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06
CPCG06Q10/04G06Q50/06
Inventor 张翼英刘飞张春光王思宁李云孙磊付兰梅彭嫚贾翠玲赵金铎童骁梁琨王聪庞浩渊阮元龙刘松尚静
Owner TIANJIN UNIV OF SCI & TECH
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