Waste mobile phone pricing method based on fuzzy neural network

Abstract

The invention provides a waste mobile phone pricing method based on a fuzzy neural network, and belongs to the field of electronic product recovery. The invention provides a waste mobile phone pricingmethod based on a fuzzy neural network in order to solve the problem that accurate pricing is difficult in the waste mobile phone recycling process. According to the invention, a feature extraction method based on principal component analysis is designed, key feature variables influencing the recovery value of the waste mobile phone are obtained, a waste mobile phone pricing model based on a fuzzy neural network is established, and nonlinear relationship description between a recovery value and a key characteristic variable is realized. The result shows that accurate pricing of the waste mobile phone can be realized in the actual recycling transaction process, and the accuracy of the pricing result can meet the requirement of efficient recycling of the waste mobile phone.

Description

technical field [0001] Based on the real transaction data of mobile phone recycling enterprises, the present invention extracts key characteristic variables that affect the recycling value of used mobile phones through a feature analysis method, and uses a fuzzy neural network to establish a pricing model of used mobile phones to realize accurate pricing of used mobile phones. There is a complex nonlinear relationship between the recycling value of used mobile phones and its influencing factors. Applying the pricing method of used mobile phones based on fuzzy neural network to the actual recycling transaction process can realize the nonlinear relationship between the recycling value of mobile phones and key characteristic variables. Accurate description and more accurate pricing results belong to the field of electronic product recycling. Background technique [0002] Waste mobile phones are rich in available resources, and the value of recycling is huge; however, there are ...

AI Technical Summary

Problems solved by technology

[0004] In the traditional pricing method of used mobile phones, the pricing parameters are mainly determined subjectively by the operator, and because the second-hand mobile phone market is underdeveloped and the transaction price information is not perfect, it is difficult to achieve satisfactory pricing results for this type of method

Methods based on mathematical models can improve the accuracy of pricing of used mobile phones. However, there is a complex nonlinear relationship between the recycling value of used mobile phones and its influencing factors. This type of method cannot accurately describe the nonlinear relationship, and the pricing results The accuracy is difficult to meet the needs of efficient recycling of used mobile phones

In recent years, in order to further improve the pricing accuracy of used mobile phones, data-driven pricing methods have attracted widespread attention. However, the used mobile phone pricing model based on BP neural network has low learning efficiency, slow convergence speed, and is easy to fall into local optimum. Realize fast and accurate pricing of used mobile phones

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