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River Water Quality Analysis and Prediction Using GBM
- Source :
- 2020 2nd International Conference on Advanced Information and Communication Technology (ICAICT).
- Publication Year :
- 2020
- Publisher :
- IEEE, 2020.
-
Abstract
- The aim of this project is to analyze and predict the quality of river water for daily usage and agricultural purpose. Water is one of the most essential elements of nature that contributes to perform biological operations of all living bodies on earth. The quality of water impacts directly on living bodies. Change in water quality causes great damage to the living species. Through this project we have schemed to detect the alteration earlier so that crucial steps can be undertaken to prevent impending losses. Taking advantage to the Gradient Boosting Model (GBM), the water quality was examined and forecasted. With the help of automatic water parameter measuring tools, samples were collected from numerous rivers of Bangladesh. The GBM was instructed utilizing the samples collected from year 2013 to 2019. The model functions using specified arguments. The model evaluates the water quality and anticipates the change that demonstrates the future water quality. The findings suggest that the model's expected values and actual values are in excellent agreement and the future change in water quality has been reported correctly.
Details
- Database :
- OpenAIRE
- Journal :
- 2020 2nd International Conference on Advanced Information and Communication Technology (ICAICT)
- Accession number :
- edsair.doi...........d537e0c2b22cdc9cbd6abaa06aabe0c7
- Full Text :
- https://doi.org/10.1109/icaict51780.2020.9333492