With the development of economy and society, the demand and use of automobiles are increasing all over the world. Cars have become a common means of transportation in people’s daily life, but with it comes the problem of automobile exhaust emission. Nowadays, motor vehicle exhaust has become one of the main sources of air pollutants in many cities. This paper mainly introduces the design and development process of a vehicle flow system based on neural network. In this paper, the demand analysis and overall analysis of the whole system are included, as well as the design and implementation of background algorithms and application functions in the system, which meet the needs of users.
With the continuous development of economy and society, the demand and use of automobiles are increasing all over the world. China’s automobile industry has gradually grown into one of the important industries. Automobile exhaust has become one of the main sources of air pollutants in many cities, and automobile exhaust in some cities has a great impact on many air pollution indicators. If we can provide a more energy-saving route for the driver before the driver leaves, combining with the traffic situation forecast, we can better realize the energy-saving and emission-reduction of automobile travel. This paper mainly introduces the web page design of an automobile energy saving and emission reduction system based on neural network, which is implemented by Python, Html, JavaScript, CSS, Java and other programming languages, and meets the basic needs of users.
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