A Classification Error Correction Method Based on Sequence Connection Model and Binary Tree Model

An error correction method and binary tree technology, applied in the field of communication network business records, can solve the problems of inability to learn, and there is a large deviation in compression and recovery, so as to reduce the workload of auditing and improve the quality of data.

Active Publication Date: 2022-02-11
WUHAN UNIV
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Problems solved by technology

By learning the characteristic relationship of the data, for the abnormal data with a small proportion, their characteristics cannot be learned, so there will be a large deviation in their compression and recovery, so as to find the abnormal record data

Method used

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  • A Classification Error Correction Method Based on Sequence Connection Model and Binary Tree Model
  • A Classification Error Correction Method Based on Sequence Connection Model and Binary Tree Model
  • A Classification Error Correction Method Based on Sequence Connection Model and Binary Tree Model

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Embodiment Construction

[0055] During specific implementation, the technical solution provided by the present invention can be realized by those skilled in the art by using computer software technology to realize the automatic operation process. The technical solution of the present invention will be described in detail below in conjunction with the drawings and embodiments.

[0056] Step 1: Data Preprocessing

[0057] First, read the communication network business records in the database based on python, use regular expressions to perform Chinese word segmentation operations on the text information in it, and store the results in different text files by field, with one word per line and deduplication; through For the word file obtained, encode the corresponding fields, and then perform a normalization operation; perform a normalization operation on the numeric fields.

[0058] Step 2: Build the Replicator Neural Network neural network model

[0059] (1) Build the input layer and output layer. The...

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Abstract

The invention relates to a classification error correction method based on a serial connection model and a binary tree model, belongs to the research category of data quality, relates to technical fields such as feed-forward neural network, RNN, and CART, and is mainly aimed at communication network service records and service channel records. Construct the Replicator Neural Network+CART classification model, use the BP optimization method for model training, and use the trained model for classification tasks. The advantages of the present invention are: automatic selection of training data, no need for manual data identification, automatic detection of abnormal data for true value recommendation, reduction of manual review workload, and improvement of data quality.

Description

technical field [0001] The invention belongs to the technical field of unsupervised classification, and in particular relates to communication network service records and channel type information generated in a power communication management system. Background technique [0002] Power communication management system: It is a dedicated power communication network system that is an important support for smart grids. It is a "two-level deployment" of headquarters and provincial companies, and a communication management system for "four-level applications" of headquarters, branches, provincial companies, and city and county companies. SG-TMS". Through standardized project construction and vigorous promotion of the practical application of the system, "SG-TMS" has been deeply integrated into the daily work of tens of thousands of power communication professionals, and has comprehensively collected the construction, operation and management of tens of thousands of equipment over t...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/35G06F40/289G06N3/08
CPCG06F16/35G06N3/084
Inventor 李石君李学礼杨济海龚红霞余伟余放甘琳李宇轩
Owner WUHAN UNIV
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