These proposed approaches to handle both issues are then used to assess the air quality prediction of the India AQI dataset using Naive Bayes (NB), KNN, and C4.5. The five treatments show that the proposed method of the Median-KNN regressor-SMOTE-Tomek Links is able to improve the...
A summation of the above-mentioned literature reveals the following problems with the previous studies in terms of air quality prediction: (1) The lockdown policy during the COVID-19 pandemic led to sudden changes in air quality, and not considering this factor may produce inadequate predictions....
Nowadays, AQI is declining, and to evaluate this there is a need for an effective AQI prediction model. This study uses two different learning algorithms, one is k-nearest neighbors (KNN), and another one is Random Forest. Both models have been used on the same dataset. Collected dataset ...
Research on air quality prediction and analysis of influencing factors also continues to grow. When conducting this research, valid, authentic, and high-quality air pollution data are necessary to obtain reasonable results. However, Missing values are unavoidable in multivariate time series due to ...
air quality prediction, combining empirical mode decomposition, long short-term memory networks, and optimization techniques, namely random search and bayesian optimization. Empirical mode decomposition is used for decomposing the actual series into a subseries to reduce the data complexity and use long ...
(a high-quality multi-scenario air quality) dataset16demonstrate superior air quality classification accuracy compared to SVM and ResNet methods, addressing the critical need for effective air quality monitoring. In this work, the utilization of exclusively daytime images, predominantly comprising sky-...
Extensive experiments on a real-world dataset demonstrate that our model achieves the highest performance compared with state-of-the-art and baseline models for air quality prediction. This is a preview of subscription content, log in via an institution to check access. Similar content being ...
Unicorn225· Community Prediction Competition ·2 years ago Late Submission more_horiz Your task is to build a machine learning model that can predict air quality index in Indian cities. Dataset Description This dataset was adapted from the Air quality dataset byRohan Rao ...
[13] conducted an inquiry spanning six years, analyzing air pollution data from 23 cities in India for the purposes of air quality examination and prediction. The dataset was pre-processed, involving the selection of pertinent features through correlation analysis. Subsequently, exploratory data ...
The datasets for each pollutant prediction were reduced in approximately 77.5% of their size through the application of PCA. In the experimental study presented in the next section, SVR will be applied both to the dataset containing all the 40 dependent variables and to the dataset that was ...