Neural network-based sharing car intelligent optimization decision method and system

Abstract

The present invention relates to a neural network-based sharing car intelligent optimization decision method and system. The neural network-based sharing car intelligent optimization decision method comprises the steps of firstly obtaining the set number of training sample pairs, wherein each training sample pair comprises an input training sample and a corresponding output desired value, then establishing a BP neural network, utilizing the training sample pairs to carry out the iterative training on the BP neural network, and finally inputting the to-be-detected input parameters in the trained BP neural network to obtain the corresponding nearest car taking position, a favorite car type, an optimal driving path, the cost-optimal consumption total price and a terminal point car returning position, help people to evaluate the travel parameters comprehensively, and decide the reasonable paths, thereby achieving the purposes of searching the optimal driving experiences and improving the vehicle selection modes, and effectively avoiding the vehicle selection and travel blindness and randomness.

Description

technical field [0001] The invention relates to a neural network-based intelligent optimization decision-making method and system for shared cars. Background technique [0002] In recent years, as people pay more and more attention to the concept of environmental protection, electric vehicles powered by electric energy are being favored by countries all over the world. Zero emission, zero pollution and excellent performance have become their main features. It is predicted that the application of electric vehicles in the future will The market will still develop by leaps and bounds. Although the advantages of electric vehicles are obvious, judging from the current situation, the number of supporting charging facilities is too small, the matching between vehicle piles is not perfect, charging safety, expensive vehicles, chaotic management of parking spaces, and scarcity of new energy licenses, etc. , is a key factor restricting the widespread use of electric vehicles among or...

AI Technical Summary

Problems solved by technology

However, when people face shared electric vehicles with different pick-up points, different models, different unit prices, and different comfort levels, they are often at a loss. How to choose their favorite models within the shortest distance according to their travel plans, and Arriving at the destination as soon as possible with the optimal driving route and the most economical total price is a problem that needs to be considered emphatically

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