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Principle of 6G Wireless Networks: Vision, Challenges and Applications
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PROGRESS AND PRECLUSION OF KNEE OSTEOARTHRITIS: A STUDY
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A Study on Various Task-Work Allocation Algorithms in Swarm Robotics
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AUTOMATION USING IOT IN GREENHOUSE ENVIRONMENT
Volume-1 | Issue-1
Principle of 6G Wireless Networks: Vision, Challenges and Applications
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Classification of Remote Sensing Image Scenes Using Double Feature Extraction Hybrid Deep Learning Approach
Volume-3 | Issue-2
Light Weight CNN based Robust Image Watermarking Scheme for Security
Volume-3 | Issue-2
Design of Digital Image Watermarking Technique with Two Stage Vector Extraction in Transform Domain
Volume-3 | Issue-3
Analysis of Natural Language Processing in the FinTech Models of Mid-21st Century
Volume-4 | Issue-3
Image Augmentation based on GAN deep learning approach with Textual Content Descriptors
Volume-3 | Issue-3
VIRTUAL REALITY GAMING TECHNOLOGY FOR MENTAL STIMULATION AND THERAPY
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A Smart Climatic Control Strategy for Optimizing Vegetable Crop Cultivation in Greenhouse using FBANN
Volume-3 | Issue-3
PROGRESS AND PRECLUSION OF KNEE OSTEOARTHRITIS: A STUDY
Volume-3 | Issue-3
Volume - 4 | Issue - 1 | march 2022
Published
25 May, 2022
In recent years, the world is being industrialized day-by-day which ultimately compels our concentration towards air quality. A gradual increase in population along with the raise in usage of vehicles and consumption of conventional energy leads to air pollution which subsequently accelerates the deterioration of air quality. And air pollution has its severe impact on human health. Many researchers have proposed various methodologies for predicting and forecasting the air quality. But it is rather important to predict the future air quality in order to reduce its impact. Therefore, this paper proposes an air quality evaluation system for future prediction. The current experiment includes three modules namely Preparation of Data, Forecasting AQI and Evaluating Air Quality. Data preparation is collecting real time data and formatting it as an input to next module. Sparse Spectrum GPR (SSGPR) is used in this study to forecast, whereas cloud model to evaluate air quality. The proposed model is capable of modelling the fuzziness and randomness. Finally, the entire model is evaluated using performance metrics like MAE, RSME and MAPE.
KeywordsAir Quality Forecasting SSGPR Fuzziness Randomness
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