Mobile communication user loss prediction method based on particle classification and BP neural network

A BP neural network, user churn technology, applied in the field of mobile communication user churn prediction, can solve problems such as difficulty in describing all user characteristics, wrong judgment, high time and space complexity, etc.

Active Publication Date: 2016-04-06
NORTHEASTERN UNIV
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Problems solved by technology

However, when these methods are applied to big data classification and prediction, they have high time and space complexity. Usually, when building a prediction model, only by analyzing

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  • Mobile communication user loss prediction method based on particle classification and BP neural network
  • Mobile communication user loss prediction method based on particle classification and BP neural network
  • Mobile communication user loss prediction method based on particle classification and BP neural network

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Embodiment Construction

[0047] An embodiment of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0048] The method for predicting the loss of mobile communication users based on particle classification and BP neural network in this embodiment, such as figure 1 shown, including the following steps:

[0049] Step 1: collecting communication record data of mobile users;

[0050] Step 2: Data preprocessing to obtain the required sample data set;

[0051] Step 2.1: Based on the communication record data of mobile users, the communication status of mobile users is counted according to the following seven attribute categories in units of months: (1) monthly call duration; (2) monthly call times; (3) monthly Basic fee; (4) monthly caller-to-call ratio; (5) network access time; (6) monthly dropped calls; (7) monthly long-distance fee;

[0052] Step 2.2: Use the quartering method to sample the communication record data of the collected mobile users, re...

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Abstract

The invention relates to a mobile communication user loss prediction method based on particle classification and a BP neural network. The method comprises: communication record data of a mobile user are collected; data pretreatment is carried out to obtain a needed sample data set; a BP neural network structure is established; on the basis of an improved particle swarm optimization (PSO) algorithm, a weight matrix and a threshold matrix of the BP neural network are initialized; a BP neural network corresponding to a particle having best fitness is trained to obtain a mobile communication user loss model; and mobile communication user loss prediction is carried out by using the mobile communication user loss model. According to the invention, the weight matrix and the threshold matrix of the BP neural network are initialized by combining application of a particle classification optimization (PCO) algorithm and a PFC process, so that the weight matrix and the threshold matrix of the BP neural network are close to global optimal values and thus the mobile user loss prediction accuracy of the BP neural network is improved.

Description

technical field [0001] The invention relates to the fields of big data and artificial intelligence, in particular to a mobile communication user loss prediction method based on particle classification and BP neural network. Background technique [0002] Nowadays, people's life is almost inseparable from mobile phones. As mobile phones provide more and more services, competition between mobile operators has become more intense. It is hard to imagine processing the data generated by hundreds of millions of mobile phone users every month, let alone extracting useful information from such a huge data set to predict user churn. Prediction of the loss of mobile communication users is very critical to the formulation of appropriate marketing strategies for mobile communication networks. Only by accurately predicting the users who will be lost can an appropriate marketing strategy be formulated to restore the users who will be lost, achieve the best benefits, and improve mobile com...

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Application Information

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IPC IPC(8): G06N3/08G06Q50/30
CPCG06N3/086G06Q50/30
Inventor 顾宁伦于瑞云姜国强安轩邈夏兴有
Owner NORTHEASTERN UNIV
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