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Xin Yin, Guorui Li and Lijun Dang Sensor Review
Lei Zhang, F. Tian, Shouqiong Liu, Jielian Guo, Bo Hu, Qi Ye, Lijun Dang, X. Peng, C. Kadri, J. Feng (2013)
Chaos based neural network optimization for concentration estimation of indoor air contaminants by an electronic noseSensors and Actuators A-physical, 189
(2013)
Chaos based neural network optimization for concentration estimation of indoor air contaminants Further reading
J. Gardner, H. Shin, E. Hines (2000)
An electronic nose system to diagnose illnessSensors and Actuators B-chemical, 70
Pingping Zhang, Jiwei Wang, X. Lv, Hui Zhang, Xuhui Sun (2015)
Facile synthesis of Cr-decorated hexagonal Co3O4 nanosheets for ultrasensitive ethanol detectionNanotechnology, 26
A. Gómez, Jun Wang, Guixian Hu, A. Pereira (2008)
Monitoring storage shelf life of tomato using electronic nose techniqueJournal of Food Engineering, 85
G. Daqi, Chen Wei (2007)
Simultaneous estimation of odor classes and concentrations using an electronic nose with function approximation model ensemblesSensors and Actuators B-chemical, 120
L. Zhang, F.C. Tian, S. Liu, J. Guo, B. Hu, Q. Ye, L. Dang, X. Peng, C. Kadri, J. Feng
Chaos based neural network optimization for concentration estimation of indoor air contaminants
S. Vito, A. Castaldo, F. Loffredo, E. Massera, T. Polichetti, I. Nasti, P. Vacca, L. Quercia, G. Francia (2007)
Gas concentration estimation in ternary mixtures with room temperature operating sensor array using tapped delay architecturesSensors and Actuators B-chemical, 124
M. Cano, Virginia Borrego, Javier Roales, J. Idígoras, T. Lopes-Costa, Palma Mendoza, J. Pedrosa (2011)
Rapid discrimination and counterfeit detection of perfumes by an electronic olfactory systemSensors and Actuators B-chemical, 156
S. Vito, E. Massera, M. Piga, L. Martinotto, G. Francia (2008)
On field calibration of an electronic nose for benzene estimation in an urban pollution monitoring scenarioSensors and Actuators B-chemical, 129
A. Berna (2010)
Metal Oxide Sensors for Electronic Noses and Their Application to Food AnalysisSensors (Basel, Switzerland), 10
Huiling Chen, Da-you Liu, Bo Yang, Jie Liu, G. Wang (2011)
A new hybrid method based on local fisher discriminant analysis and support vector machines for hepatitis disease diagnosisExpert Syst. Appl., 38
Frank Röck, N. Bârsan, U. Weimar (2008)
Electronic nose: current status and future trends.Chemical reviews, 108 2
Lei Zhang, F. Tian, C. Kadri, Bo Xiao, Hongjuan Li, Lina Pan, Hongwei Zhou (2011)
On-line sensor calibration transfer among electronic nose instruments for monitoring volatile organic chemicals in indoor air qualitySensors and Actuators B-chemical, 160
B. Ehret, Konstantin Safenreiter, F. Lorenz, J. Biermann (2011)
A new feature extraction method for odour classificationSensors and Actuators B-chemical, 158
S. Ampuero, J. Bosset (2003)
The electronic nose applied to dairy products: a reviewSensors and Actuators B-chemical, 94
Byeongdeok Yea, T. Osaki, K. Sugahara, R. Konishi (1997)
The concentration-estimation of inflammable gases with a semiconductor gas sensor utilizing neural networks and fuzzy inferenceSensors and Actuators B-chemical, 41
Lei Zhang, F. Tian, Hong Nie, Lijun Dang, Guorui Li, Qi Ye, C. Kadri (2012)
Classification of multiple indoor air contaminants by an electronic nose and a hybrid support vector machineSensors and Actuators B-chemical, 174
S. Guney, A. Atasoy (2012)
Multiclass classification of n-butanol concentrations with k-nearest neighbor algorithm and support vector machine in an electronic noseSensors and Actuators B-chemical, 166
G. Huyberechts, P. Szecówka, J. Roggen, B. Licznerski (1997)
Simultaneous quantification of carbon monoxide and methane in humid air using a sensor array and an artificial neural networkSensors and Actuators B-chemical, 45
Hui Yu, Jun Wang (2007)
Discrimination of LongJing green-tea grade by electronic noseSensors and Actuators B-chemical, 122
Daqi Gao, Zeping Yang, Chaoqian Cai, Fangjun Liu (2012)
Performance evaluation of multilayer perceptrons for discriminating and quantifying multiple kinds of odors with an electronic noseNeural networks : the official journal of the International Neural Network Society, 33
(2011)
A new feature extraction method for odour classification ” , Sensors and Actuators B
A. D'Amico, G. Pennazza, M. Santonico, E. Martinelli, C. Roscioni, G. Galluccio, R. Paolesse, C. Natale' (2010)
An investigation on electronic nose diagnosis of lung cancer.Lung cancer, 68 2
K. Brudzewski, S. Osowski, A. Golembiecka (2012)
Differential electronic nose and support vector machine for fast recognition of tobaccoExpert Syst. Appl., 39
Lei Zhang, F. Tian, C. Kadri, Guangshu Pei, Hongjuan Li, Lina Pan (2011)
Gases concentration estimation using heuristics and bio-inspired optimization models for experimental chemical electronic noseSensors and Actuators B-chemical, 160
C. Natale, A. Macagnano, F. Davide, A. D'Amico, R. Paolesse, T. Boschi, M. Faccio, G. Ferri (1997)
An electronic nose for food analysisSensors and Actuators B-chemical, 44
M. Pardo, G. Faglia, G. Sberveglieri, M. Corte, F. Masulli, M. Riani (2000)
A time delay neural network for estimation of gas concentrations in a mixtureSensors and Actuators B-chemical, 65
Purpose – The purpose of this paper is to present a novel concentration estimation model for improving the accuracy and robustness of low‐cost electronic noses (e‐noses) with metal oxide semiconductor sensors in indoor air contaminant monitoring and overcome the potential sensor drift. Design/methodology/approach – In the quantification model, a piecewise linearly weighted artificial neural network ensemble model (PLWE‐ANN) with an embedded self‐calibration module based on a threshold network is studied. Findings – The nonlinear estimation problem of sensor array‐based e‐noses can be effectively transformed into a piecewise linear estimation through linear weighted neural networks ensemble activated by a threshold network. Originality/value – In this paper, a number of experimental results have been presented, and it also demonstrates that the proposed model has very good accuracy and robustness in real‐time indoor monitoring of formaldehyde.
Sensor Review – Emerald Publishing
Published: Jun 10, 2014
Keywords: Sensors; Gas; Neural networks; Arrays; Multi‐sensor systems
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