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Simulation and optimization of artificial neural network based air quality estimator


Article Information

Title: Simulation and optimization of artificial neural network based air quality estimator

Authors: Shirish Pandey, S. Hasan Saeed, Shailendra Kumar

Journal: ARPN Journal of Engineering and Applied Sciences

HEC Recognition History
Category From To
Y 2023-07-01 2024-09-30
Y 2022-07-01 2023-06-30
Y 2021-07-01 2022-06-30
X 2020-07-01 2021-06-30

Publisher: Khyber Medical College, Peshawar

Country: Pakistan

Year: 2019

Volume: 14

Issue: 14

Language: English

Categories

Abstract

Electronic noses are designed to classify odors. It aims to provide remote connectivity, data storage and signal processing. In this research work an AI technique using ANN in use of sensor array grid system concerning air pollution monitoring of the carbon monoxide (CO) gas by integration of distributed sensors, data records and configuring ANN model. The analysis and the characterization acquired by prototype of multi-sensors electronic nose which have TGS 822, TGS 2442, TGS 813, TGS 4160, TGS 2600 sensors along with temperature, humidity and wind speed measurements sensors. Regression and MSE are taken as performance parameter to find best possible ANN model that can correlate in between sensor response and CO concentration as pollutants, evaluated by Mat Lab software and statistical analysis. The influence of data segment length is taken into account to improve the model. The variation in hidden layer nodes performed and compared using the variable length data then the mean square error (mse) is calculated.


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