A system and method for haze prediction based on bp neural network

Abstract

The present invention provides a system and method for haze prediction based on BP neural network, the system includes: mining the relationship between collected air quality data through BP neural network, predicting air quality and haze weather development trend, and Haze weather provides early warning; It is characterized in that: comprise data collection module, database, data arrangement module, haze prediction server, data preprocessing module, neuron learning module, BP neural network prediction module, WEB server and mobile terminal; Its method Yes: describe the haze prediction system as a multi-input multi-output self-learning prediction system, input the collected haze and air quality data, and predict the possible development trend of haze weather through the self-learning and self-adaptive ability of the neural network, And reduce the prediction error; the present invention can use the existing haze observation data to predict the haze development, and can deeply dig the complex relationship between the input data, so as to obtain a more accurate prediction effect.

Description

technical field [0001] The invention relates to a haze prediction method and technology, in particular to a haze prediction system and method based on a BP neural network. Background technique [0002] At present, the haze phenomenon in China has attracted more and more attention, and researches on haze prediction analysis and governance strategies have emerged in an endless stream. implementation etc. The current haze prediction methods and systems mainly focus on the monitoring of ecological environment and air quality indicators for modeling, and use the monitored indicators such as PM2.5 and PM1.0 to try to accurately describe the mathematical model and evolution mechanism of haze. The latest technology also includes the deployment of sensor networks in haze-prone areas and satellite image analysis technologies, which provide a large amount of accurate data for haze monitoring and early warning, and then use this as a basis to analyze and predict the development trend o...

AI Technical Summary

Problems solved by technology

Moreover, the natural environment and social environment where the haze is located have a self-learning nature, which is difficult for traditional forecasting methods to take into account

In China, with the application of data processing technology in haze prediction, it provides conditions for the use of data collection and self-learning methods to predict haze. However, there are few haze prediction methods and systems based on BP neural network in the market

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