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Subway fault association recommendation method based on prior weight and multi-layer TFP algorithm

A recommendation method and fault technology, applied in the direction of calculation, response error generation, instrumentation, etc., can solve the problems that cannot be suggested by users, and the algorithm cannot be well adapted

Inactive Publication Date: 2021-08-31
SOUTHWEST JIAOTONG UNIV +1
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Problems solved by technology

However, these single algorithms cannot be well adapted to the multi-layer data structure of the subway catenary fault data, and it is very likely to return a large number of strong association rules to the user, so it cannot provide good advice to the user effect

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  • Subway fault association recommendation method based on prior weight and multi-layer TFP algorithm

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Embodiment Construction

[0034] The technical solution of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0035] The subway fault association recommendation method based on prior weight and multi-layer TFP algorithm is characterized in that: comprising the following steps:

[0036]The basic data processing step is to analyze the catenary fault data collected on site, and encode all the fault data. In this embodiment, when encoding the fault data, it can be encoded according to the user-defined encoding rules, and after the encoding is completed , forming a fault database divided into three layers, the three layers of data layers in the fault database are respectively: fault type layer, fault equipment layer and fault attribute layer; the data in the fault database completed by coding is carried out according to the needs of users set generation operation to obtain the preprocessed transaction set data; in this embodiment, the encoding rules can ...

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Abstract

The invention discloses a subway fault correlation recommendation method based on a priori weight and a multi-layer TFP algorithm, and relates to the technical field of traction power supply systems in rail transit. The present invention first analyzes the catenary fault data collected on site, encodes all fault types according to the corresponding coding rules, and divides the fault data into three layers of fault databases, namely fault type layer, fault equipment layer and fault attribute layer. According to the layered characteristics of the data, according to the site conditions of the subway fault, the corresponding weights are formulated and the weights of each item in each layer are calculated to generate the corresponding association rules. Using the generated strong association rule base, the top-k is excavated on the basis of it The most frequent patterns to achieve the purpose of reducing the number of patterns returned by mining, and finally return the k strongly correlated fault rules with the highest support to the user.

Description

technical field [0001] The invention relates to the technical field of traction power supply systems in rail transit, and more specifically relates to a subway fault association recommendation method based on prior weight multi-layer TFP algorithm. Background technique [0002] From the perspective of the entire current catenary research field, the correlation analysis for catenary fault data is still in its infancy. As far as the existing technical literature is concerned, there is no public technical solution in this field that can effectively analyze the catenary of the subway. Therefore, it is impossible to form a relatively complete association rule base for various faults of the subway, and thus it is impossible to provide good maintenance suggestions for the subway operation site. [0003] From the perspective of fault data, most of the current research stays at the stage of coding standard research, and cannot establish a relatively standardized and systematic data s...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/26G06F11/07
CPCG06F11/0766G06F11/0781G06F16/26
Inventor 于龙刘兰刘一谷赖声钢李政蒋中志李正国康学剑
Owner SOUTHWEST JIAOTONG UNIV
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