Analysis and evaluation of the regional air quality index forecasting based on web-text sentiment analysis method

Quality analysis is the science of in-depth monitoring supported by interactive visual interfaces, and it has many applications in environmental fields. According to nature, both manual and natural issues do not adequately understand the danger factor monitoring approach since they cannot correctly take all the information as an accessible one. Therefore, this paper suggests a web-text analysis based regional air quality index forecasting (WEBT-RAQIF) method for the air quality index monitoring development and evaluation of pollution research. In the context of acquiring a system familiar to a large number of research experiments, a web-text analysis method has developed to support monitoring and analysis issues. In this process, the added benefit of web-text has been illustrated by contrasting traditional monitoring approaches with immersive web-text analysis techniques through various user domains. The empirical evidence of the added value for general monitoring has been analyzed by web-text analysis

Automated summary

This paper proposes a web-text analysis based method for developing and evaluating air quality index monitoring and pollution research. The added value of web-text analysis has been demonstrated by comparing traditional monitoring approaches with immersive techniques.