Waste mobile phone pricing method based on value preserving rate and discrete neural network

A neural network and BP neural network technology, applied in the field of electronic product recycling, can solve the problems of unstable prediction results and difficult convergence of price prediction models, and achieve the effects of stable training, parameter saving and accurate prediction results.

Pending Publication Date: 2021-01-05
中国物资再生协会
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AI Technical Summary

Problems solved by technology

[0006] Aiming at the problems that the existing neural network price prediction model is difficult to converge and the prediction results a...

Method used

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  • Waste mobile phone pricing method based on value preserving rate and discrete neural network
  • Waste mobile phone pricing method based on value preserving rate and discrete neural network
  • Waste mobile phone pricing method based on value preserving rate and discrete neural network

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Embodiment Construction

[0048] Below in conjunction with accompanying drawing and specific embodiment, the present invention is further described:

[0049] The present invention adopts following technical scheme and implementation steps:

[0050] (1) Calculation of preservation rate

[0051] Generally, new mobile phones are sold at their official selling prices. As time goes by, they will wear out and their prices will continue to decrease. The ratio of recycling prices to new phone prices changes over time. The value preservation rate of machine price is defined as follows:

[0052]

[0053] Among them, s is the preservation rate, v is the new machine price, and p is the recycling price. Because the recycling price is always lower than the price of the new machine, the value range of the preservation rate s is [0,1]. At the same time, according to the preservation rate s and the new machine price v, the recovery price can be calculated as:

[0054] p=vs (2)

[0055] (2) Feature extraction of...

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Abstract

The invention discloses a waste mobile phone pricing method based on a value preserving rate and a discrete neural network, belongs to the field of electronic product recovery, and solves the problemthat waste mobile phone recovery is difficult to accurately price. According to the method, the predicted price of the waste mobile phone is converted into the predicted value retention rate of the waste mobile phone, so that the prediction space of the neural network is fixed, and the prediction effect is more accurate; the characteristics influencing the recovery price of the waste mobile phoneare generally discrete values, and the discrete neural network model designed by the invention densifies the discrete characteristics in a self-adaptive manner, extracts the key information of the discrete characteristics, and realizes the conversion from the characteristics of the waste mobile phone to the value preserving rate in an end-to-end manner; and the price of the waste mobile phone canbe efficiently evaluated, the feasibility of the method is verified through testing, and the method has important application value.

Description

technical field [0001] The invention belongs to the field of electronic product recycling, and is based on a large amount of transaction data of a waste mobile phone recycling platform, trains a neural network, and realizes price evaluation of waste mobile phones. The method inputs the discrete features that affect the recycling price of used mobile phones into the discrete neural network model designed by the present invention, adaptively densifies the discrete features, extracts the key information of the discrete features, and realizes the conversion from the features of used mobile phones to the value preservation rate, and then based on the value preservation Calculate the recycling price based on the recycling rate, establish a prediction model between the discrete characteristics of used mobile phones and the value retention rate, and accurately realize the price evaluation of used mobile phones. Background technique [0002] Waste mobile phones contain abundant recyc...

Claims

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Application Information

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IPC IPC(8): G06Q30/02G06Q10/00G06N3/08G06N3/04G06Q10/04
CPCG06Q30/0283G06Q10/30G06N3/084G06Q10/04G06N3/045Y02W30/82Y02W90/00
Inventor 于可利张贺然刘雨浓
Owner 中国物资再生协会
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