Electronic product asynchronous adaptive value evaluation method based on deep neural network

Abstract

The invention relates to an electronic product asynchronous adaptive value evaluation method based on a deep neural network, which is used for solving the problem of automatic pricing of a second-handelectronic product. A valuation module used for estimating the value of a product and a self-adaptive price adjustment module used for carrying out pricing adjustment for coping with market changes are provided, the self-adaptive price adjustment module uses a double-depth Q network, and the model structure of the self-adaptive price adjustment module is composed of two deep Q learning networks with the same structure and different parameters, namely a behavior network and a target network; and the valuation module obtains the basic valuation of the product at the moment t according to the internal attributes influencing the price of the electronic product, and the estimated price output by the valuation module is adjusted by the price adjustment action at selected by the self-adaptive price adjustment module to obtain the final price. The pricing is adaptively adjusted to adapt to the rapidly changing market, the price rationality is ensured, and the transaction rate is improved.

Description

technical field [0001] The invention relates to the field of recycling and utilization of renewable resources, in particular to an asynchronous self-adaptive value evaluation method for second-hand electronic products based on a deep neural network. Background technique [0002] In recent years, with the rapid development of science and technology, there are endless types of electronic products. At the same time, with the development of the Internet, e-commerce is gradually rising, and more and more users choose to shop online. Due to the real-time and convenience of Internet information acquisition, users can check and compare the pricing, preferential measures and sales of various platforms through the Internet before deciding whether to buy. The price of electronic products will continue to change over time. For electronic product sellers, it is necessary to obtain a certain price advantage in this game with competitors. The method of accurate pricing after comprehensiv...

AI Technical Summary

Problems solved by technology

In the traditional used mobile phone pricing process, complex model formulation and market factors are considered in the final pricing process, all rely on experienced professionals

[0004] Conventional product pricing methods are poor in accuracy and real-time performance, requiring manual intervention in the pricing process

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