INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15
By utilizing machine learning to estimate the air quality index of a certain place, we forecast India's air quality. The air quality index of India is a commonly used indicator of pollution levels (so2, no2, rspm, spm, etc.) through time. Based on historical data from prior years and utilizing ML techniques, we created a model to forecast the air quality index for a certain forthcoming year. For our prediction problem, we use cost estimation to increase the model's efficacy. When given historical data on pollutant concentration, our model will be able to accurately estimate the air quality index for an entire county, any state, or any contiguous region. We improved performance over the baseline regression models in our model by applying the suggested parameter-reducing formulations. Our model has a 91% accuracy rate when used to estimate the air quality index for the entirety of India. We also utilise the AHP MCDM approach to determine the order of preference based on how closely it resembles the ideal solution. This research can assist in building MDS by utilising deep learning techniques like XGBoost, Random Forest (RF), and Convolution Neural Network (CNN), which can monitor the information entering mobile devices and separate out unlawful occurrences. With an accuracy rate of roughly 90%, CNN outperforms the other algorithms among the two techniques. Air quality prediction is carried out in our project.
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Cite Article:
"Air Quality Prediction Using Statistical Model Built On Machine Learning.", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 4, page no.1291 - 1295, April-2023, Available :http://www.ijsdr.org/papers/IJSDR2304209.pdf
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000337209
Publication Details:
Published Paper ID: IJSDR2304209
Registration ID:205389
Published In: Volume 8 Issue 4, April-2023
DOI (Digital Object Identifier):
Page No: 1291 - 1295
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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