{'fraction_non_alphanumeric': 0.022988505747126436, 'fraction_numerical': 0.019704433497536946, 'mean_word_length': 4.809523809523809, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Neural Network and Machine Learning based Prediction Model Design for Air Pollutant PM10

The AOI is the measure of pollutants contained in the air. The various pollutants which are generally present in the air are SO2, NO2, ozone, CO, PM10 and PM25. The present research work is using the secondary data pertaining to the air quality of Uttarakhand. The goal of this work is to design prediction models for predicting the PM10 value given the SO2 and NO2 concentrations. ANN (artificial neural network) and ML (machine learning) based prediction models are designed in MATLAB, and their outputs are compared.