Quantification of Individual Gas Components for Gas Sensor Array using Neural Networks with Levenberg–Marquardt (LM) and Bayesian Regularization (BR) Technique-Reference-Cited by-同舟云学术

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Quantification of Individual Gas Components for Gas Sensor Array using Neural Networks with Levenberg–Marquardt (LM) and Bayesian Regularization (BR) Technique

Published:2023-07-06 Issue: Volume: Page:
ISSN:
Container-title:2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)
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Author:

Ansari Ghazala¹,Singh Rupali¹

Affiliation:

1. SRM Institute of Science and Technology,Faculty of Engineering and Technology,Department of Electronics & Communication Engineering,Ghaziabad,Uttar Pradesh,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10306338/10306339/10306658.pdf?arnumber=10306658

Reference30 articles.

1. CO, NO2 and NOx urban pollution monitoring with on-field calibrated electronic nose by automatic bayesian regularization

2. Calibration of microhotplate conductometric gas sensors by non-linear multivariate regression methods

3. Vehicular Intelligence System: Time-Based Vehicle Next Location Prediction in Software-Defined Internet of Vehicles (SDN-IOV) for the Smart Cities

4. An evaluation of orthogonal signal correction applied to calibration transfer of near infrared spectra

5. A practical Bayesian framework for back-propagation networks;mackay;Neural Comput,1992

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