GEOSPATIAL ARTIFICIAL INTELLIGENCE (GEOAI)
RANDOM FOREST TECHNOLOGY
Random forest technology is a widely employed machine learning algorithm that amalgamates outcomes from multiple datasets to produce a final output.
In the context of air quality prediction, researchers utilize historical data amassed from diverse air quality monitoring stations across a city. If you get the admission best IIT-JEE coaching in Delhi, So click here know about us https://toppersacademy.app/top-iit-jee-coaching-in-delhi/
By employing the random forest algorithm, they forecast the Air Quality Index with enhanced accuracy and reliability.
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MORE ABOUT THE NEWS:
During the India Clean Air Summit (ICAS), an event focused on addressing air quality issues, the National Institute of Advanced Studies (NIAS), Bengaluru, introduced this innovative initiative.
GeoAI employs artificial intelligence, satellite imagery, mobile technology, and citizen science to pinpoint sources of air pollution.
This pilot project aims to evolve into a predictive tool for effectively monitoring air quality within the city. By utilizing historical data and employing conventional artificial neural network techniques, the project team develops a robust predictive model.
The initiative operates within a comprehensive geospatial framework, integrating various data sources into a curated database. Beyond addressing air pollution, the project aligns with broader sustainable development goals (SDGs), encompassing issues like water pollution and electromagnetic radiation.
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