A BP neural network used car price evaluation algorithm based on improved ant colony algorithm

Abstract

The invention discloses a BP neural network used car price evaluation algorithm based on ant colony algorithm optimization. The method comprises the steps of: choosing a three-layer BP neural networkas the prototype, adopting improved ant colony algorithm to optimize the weight initialization process of BP neural network, and establishing a used car price evaluation model. The concrete steps areas follows: 1. performing data collection and pretreatment; 2, determining a network topology; 3, optimizing the weight initialization process of the BP neural network by adopting the improved ant colony algorithm; Step 4: Further training the optimized BP neural network to predict the used car price. The invention provides a BP neural network used car price evaluation algorithm based on ant colony optimization. Compared with the traditional algorithm, the BP neural network used car price evaluation algorithm can improve the defects of easily falling into local optimization, slow convergence speed, oscillation effect and the like in the BP neural network, thereby establishing an on-line vehicle price evaluation system with practical value.

Description

technical field [0001] The invention relates to a second-hand car price evaluation algorithm based on an improved ant colony BP neural network, which belongs to the field of computer applications. Background technique [0002] Against the background of the increasing development of network marketing and Internet big data theory, combined with the growing demand of Chinese people for private cars, large-scale used car trading platforms based on neural networks have been rapidly promoted and applied. Under such a platform trading system, by analyzing and adjusting various parameters that need to be considered in the used car trading market, and establishing a suitable neural network model, the accuracy of the entire used car trading price evaluation can be improved. As big data-related technologies are widely used in the fields of machine learning and cognitive science, the BP neural network algorithm, as a calculation model mainly used to estimate and approximate functions, c...

AI Technical Summary

Problems solved by technology

Most of these existing valuation algorithms are too empirical, do not have much theoretical basis, and do not actively disclose the details of the algorithms. There are defects such as low algorithm transparency, low valuation efficiency, and low calculation accuracy. The dynamic changes of the data are reflected in the calculation process, and these are the key factors in determining the price of used cars

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