Civil aviation field passenger value prediction method

A passenger and value technology, applied in the field of civil aviation passenger management, to achieve the effect of improving the retention rate and enhancing the competitiveness of enterprises

Inactive Publication Date: 2019-03-26
BEIJING JIAOTONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] At present, there is no effective method for predictin

Method used

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  • Civil aviation field passenger value prediction method
  • Civil aviation field passenger value prediction method
  • Civil aviation field passenger value prediction method

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Embodiment 1

[0047] The embodiment of the present invention proposes a method of modeling customer life cycle value, calculating user value and predicting user's future value according to customer historical behavior. The present invention can closely link customer behavior with enterprise interests, fully consider the influence of user behavior on user value, predict the future value of users more accurately, help enterprises discover potential value of users, and improve customer retention rate.

[0048] The present invention utilizes a deep learning algorithm to construct CLTV (Customer Lifetime value; customer statement period value) model and RFUM (Recency, Frequency, Unit revenue per kilometers, Kilometers respectively) for data such as user's consumption behavior and consumption habits in the historical time window; Recent consumption time, recent consumption frequency, income per kilometer, number of kilometers) model, using the AHP (Analytic hierarchy process; Analytic Hierarchy Pr...

Embodiment 2

[0080] S1. Collect data and perform data preprocessing. There are two datasets. The basic data set comes from the data collection system of Civil Aviation of China, covering the entire sample within two years, and contains 30 features, including recent purchase behavior, customer preference and volume statistics. Due to the relationship between individual activities and regional economies, the external dataset includes city categories, regions, and GDP. In the process of data preprocessing, in order to reduce the training cost and ensure the consistency with the real distribution, stratified sampling is adopted to extract the data of 2 million traveling passengers. In feature engineering, different encoding methods are used for different types of features, and all types of variables are encoded using One-Hot encoding. For continuous variables other than R, F, U, M, standard feature scaling is used. For R, F, U, M, use the method of dispersion standardization to standardize ...

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Abstract

The invention provides a civil aviation field passenger value prediction method. According to the method, the client value of the civil aviation field is evaluated from four dimensions; Secondly, a numerical quantization model is put forward, multi-dimensional features of the RFUM model are converted into a one-dimensional numerical space through the AHP decision process, and user value changes can be analyzed from the numerical angle; And finally, proposing a sequence-dependent multi-task learning model, considering the natural correlation between the user consumption intention and the consumption amount, and predicting the future value of the user by utilizing the time sequence characteristics of the historical consumption data of the user and combining a time sequence data attention mechanism and a multi-task learning process. Implementation of the method is combined with marketing requirements in the civil aviation field, the life cycle value of the enterprise client can be predicted more accurately, and based on the prediction result, the enterprise can better formulate a client expansion strategy, the user retention rate is increased, the client value is utilized to the maximum extent, and the enterprise competitiveness is enhanced.

Description

technical field [0001] The invention relates to the technical field of civil aviation passenger management, in particular to a method for predicting passenger value in the civil aviation field. Background technique [0002] In recent years, with the rapid development of China's civil aviation field, 58 airlines have gradually been attracted to the domestic market to compete for market share. With the increasingly fierce competition among enterprises, how to expand and consolidate customer resources has become the most concerned issue for enterprises. In such an environment, it is not enough for companies to adjust their marketing strategies simply by analyzing the value that customers have demonstrated through various statistical analysis methods. If airlines can predict the future value of passengers or discover the future value growth of passengers in advance during the rapid growth of civil aviation passengers, they can gain more benefits. [0003] High-value customer gr...

Claims

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Application Information

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IPC IPC(8): G06F16/28G06N3/08G06Q30/02
CPCG06N3/084G06Q30/0202
Inventor 韩升林友芳武志昊万怀宇董兴业王晶
Owner BEIJING JIAOTONG UNIV
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