{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T19:57:11Z","timestamp":1776801431693,"version":"3.51.2"},"reference-count":33,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2018,6,12]],"date-time":"2018-06-12T00:00:00Z","timestamp":1528761600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["XDJK2017C073"],"award-info":[{"award-number":["XDJK2017C073"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61672436, 61571372"],"award-info":[{"award-number":["61672436, 61571372"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In this paper, a novel feature selection and fusion framework is proposed to enhance the discrimination ability of gas sensor arrays for odor identification. Firstly, we put forward an efficient feature selection method based on the separability and the dissimilarity to determine the feature selection order for each type of feature when increasing the dimension of selected feature subsets. Secondly, the K-nearest neighbor (KNN) classifier is applied to determine the dimensions of the optimal feature subsets for different types of features. Finally, in the process of establishing features fusion, we come up with a classification dominance feature fusion strategy which conducts an effective basic feature. Experimental results on two datasets show that the recognition rates of Database I and Database II achieve 97.5% and 80.11%, respectively, when k = 1 for KNN classifier and the distance metric is correlation distance (COR), which demonstrates the superiority of the proposed feature selection and fusion framework in representing signal features. The novel feature selection method proposed in this paper can effectively select feature subsets that are conducive to the classification, while the feature fusion framework can fuse various features which describe the different characteristics of sensor signals, for enhancing the discrimination ability of gas sensors and, to a certain extent, suppressing drift effect.<\/jats:p>","DOI":"10.3390\/s18061909","type":"journal-article","created":{"date-parts":[[2018,6,12]],"date-time":"2018-06-12T10:58:32Z","timestamp":1528801112000},"page":"1909","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["Enhancing the Discrimination Ability of a Gas Sensor Array Based on a Novel Feature Selection and Fusion Framework"],"prefix":"10.3390","volume":"18","author":[{"given":"Changjian","family":"Deng","sequence":"first","affiliation":[{"name":"College of Electronic and Information Engineering, Southwest University, Chongqing 400715, China"}]},{"given":"Kun","family":"Lv","sequence":"additional","affiliation":[{"name":"High Tech Department, China International Engineering Consulting Corporation, Beijing 100048, China"}]},{"given":"Debo","family":"Shi","sequence":"additional","affiliation":[{"name":"Westa College, Southwest University, Chongqing 400715, China"}]},{"given":"Bo","family":"Yang","sequence":"additional","affiliation":[{"name":"College of Electronic and Information Engineering, Southwest University, Chongqing 400715, China"}]},{"given":"Song","family":"Yu","sequence":"additional","affiliation":[{"name":"College of Electronic and Information Engineering, Southwest University, Chongqing 400715, China"}]},{"given":"Zhiyi","family":"He","sequence":"additional","affiliation":[{"name":"College of Electronic and Information Engineering, Southwest University, Chongqing 400715, China"}]},{"given":"Jia","family":"Yan","sequence":"additional","affiliation":[{"name":"College of Electronic and Information Engineering, Southwest University, Chongqing 400715, China"}]}],"member":"1968","published-online":{"date-parts":[[2018,6,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1016\/0925-4005(94)87085-3","article-title":"A brief history of electronic nose","volume":"18","author":"Gardner","year":"1994","journal-title":"Sens. Actuators B"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1016\/S0925-4005(01)00787-0","article-title":"The evaluation of quality of post-harvest oranges and apples by means of an electronic nose","volume":"78","author":"Natale","year":"2001","journal-title":"Sens. Actuators B Chem."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"442","DOI":"10.1016\/S0043-1354(98)00245-0","article-title":"Characterisation of wastewater using an electronic nose","volume":"33","author":"Stuetz","year":"1999","journal-title":"Water Res."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"4899","DOI":"10.3390\/s110504899","article-title":"Use of the Electronic Nose as a Screening Tool for the Recognition of Durum Wheat Naturally Contaminated by Deoxynivalenol: A Preliminary Approach","volume":"11","author":"Campagnoli","year":"2011","journal-title":"Sensors"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1016\/j.snb.2007.12.019","article-title":"Fungal volatile fingerprints: Discrimination between dermatophyte species and strains by means of an electronic nose","volume":"131","author":"Sahgal","year":"2008","journal-title":"Sens. Actuators B Chem."},{"key":"ref_6","first-page":"307","article-title":"Discrimination of selected fungi species based on their odour profile using prototypes of electronic nose instruments","volume":"116","year":"2017","journal-title":"Measurement"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1016\/j.snb.2014.09.115","article-title":"Human breath-print identification by E-nose, using information-theoretic feature selection prior to classification","volume":"217","author":"Wang","year":"2015","journal-title":"Sens. Actuators B Chem."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1016\/S0004-3702(97)00043-X","article-title":"Wrappers for feature subset selection","volume":"97","author":"Kohavi","year":"1997","journal-title":"Artif. Intell."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"472","DOI":"10.1016\/j.snb.2009.11.036","article-title":"A sensor conditioning principle for odor identification","volume":"146","author":"Muezzinoglu","year":"2010","journal-title":"Sens. Actuators B Chem."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1146\/annurev-anchem-062011-143205","article-title":"Sensor Array Design for Complex Sensing Tasks","volume":"8","author":"Johnson","year":"2015","journal-title":"Annu. Rev. Anal. Chem."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"471","DOI":"10.1016\/j.snb.2013.01.088","article-title":"Optimal feature selection for classifying a large set of chemicals using metal oxide sensors","volume":"187","author":"Nowotny","year":"2013","journal-title":"Sens. Actuators B Chem."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"353","DOI":"10.1016\/j.snb.2015.02.025","article-title":"Feature selection and analysis on correlated gas sensor data with recursive feature elimination","volume":"212","author":"Yan","year":"2015","journal-title":"Sens. Actuators B Chem."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Shahid, A., Choi, J.H., Rana, A.U.H.S., and Kim, H.S. (2018). Least Squares Neural Network-Based Wireless E-Nose System Using an SnO2 Sensor Array. Sensors, 18.","DOI":"10.3390\/s18051446"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"476","DOI":"10.1016\/j.snb.2018.02.144","article-title":"Odor Control Map: Self Organizing Map built from electronic nose signals and integrated by different instrumental and sensorial data to obtain an assessment tool for real environmental scenarios","volume":"263","author":"Licen","year":"2018","journal-title":"Sens. Actuators B Chem."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Lippolis, V., Cervellieri, S., and Damascelli, A. (2018). Rapid prediction of deoxynivalenol contamination in wheat bran by MOS-based electronic nose and characterization of the relevant pattern of volatile compounds. J. Sci. Food Agric.","DOI":"10.1002\/jsfa.9028"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1226","DOI":"10.1109\/TPAMI.2005.159","article-title":"Feature selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy","volume":"27","author":"Peng","year":"2005","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/S0924-4247(00)00419-2","article-title":"Extraction and selection of parameters for evaluation of breath alcohol measurement with an electronic nose","volume":"84","author":"Paulsson","year":"2000","journal-title":"Sens. Actuators A Phys."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"5747","DOI":"10.1109\/JSEN.2016.2568209","article-title":"Using Field Asymmetric Ion Mobility Spectrometry for Odor Assessment of Automobile Interior Components","volume":"16","author":"Li","year":"2016","journal-title":"IEEE Sens. J."},{"key":"ref_19","first-page":"103","article-title":"Manifold Regularized Multi-View Feature Selection for Web Image Annotation","volume":"204","author":"Li","year":"2014","journal-title":"Adv. Multimed. Inf. Process. PCM"},{"key":"ref_20","first-page":"316","article-title":"Feature Selection Based on Minimum Overlap Probability (MOP) in Identifying Beef and Pork","volume":"7","author":"Anwar","year":"2016","journal-title":"Int. J. Adv. Comput. Sci. Appl."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"130","DOI":"10.1186\/s13638-016-0623-3","article-title":"Ensemble-based multi-filter feature selection method for DDoS detection in cloud computing","volume":"1","author":"Osanaiye","year":"2016","journal-title":"Eurasip J. Wirel. Commun. Netw."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"3424","DOI":"10.1007\/s12161-017-0909-z","article-title":"Evaluation of Industrial Roasting Degree of Coffee Beans by Using an Electronic Nose and a Stepwise Backward Selection of Predictors","volume":"10","author":"Giungato","year":"2017","journal-title":"Food Anal. Method"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Zhi, R., Zhao, L., and Zhang, D. (2017). A Framework for the Multi-Level Fusion of Electronic Nose and Electronic Tongue for Tea Quality Assessment. Sensors, 17.","DOI":"10.3390\/s17051007"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1016\/j.jfoodeng.2013.11.008","article-title":"Detection of adulteration in cherry tomato juices based on electronic nose and tongue: Comparison of different data fusion approaches","volume":"126","author":"Hong","year":"2014","journal-title":"J. Food Eng."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1016\/j.talanta.2018.01.096","article-title":"E-nose, e-tongue and e-eye for edible olive oil characterisation and shelf life assessment: A powerful data fusion approach","volume":"182","author":"Buratti","year":"2018","journal-title":"Talanta"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1016\/j.foodchem.2014.01.021","article-title":"Evaluation of Oxygen Exposure Levels and Plyphenolic Content of Red Wines Using an Electronic Panel Formed by an Electronic Nose and an Electronic Tongue","volume":"155","author":"Apetrei","year":"2014","journal-title":"Food Chem."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1016\/j.sna.2013.12.029","article-title":"A novel classifier ensemble for recognition of multiple indoor air contaminants by an electronic nose","volume":"207","author":"Dang","year":"2014","journal-title":"Sens. Actuators A Phys."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"16027","DOI":"10.3390\/s150716027","article-title":"Optimal Sensor Selection for Classifying a Set of Ginsengs Using Metal-Oxide Sensors","volume":"15","author":"Miao","year":"2015","journal-title":"Sensors"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"740","DOI":"10.1016\/j.cap.2010.11.051","article-title":"Comparison of k-nearest neighbor, quadratic discriminant and linear discriminant analysis in classification of electromyogram signals based on the wrist-motion directions","volume":"11","author":"Kim","year":"2011","journal-title":"Curr. Appl. Phys."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1016\/j.enconman.2013.01.033","article-title":"A new approach to very short-term wind speed prediction using k-nearest neighbor classification","volume":"69","author":"Yesilbudak","year":"2013","journal-title":"Energy Convers. Manag."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1016\/j.snb.2011.04.069","article-title":"A background elimination method based on wavelet transform in wound infection detection by electronic nose","volume":"157","author":"Feng","year":"2011","journal-title":"Sens. Actuators B Chem."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"320","DOI":"10.1016\/j.snb.2012.01.074","article-title":"Chemical gas sensor drift compensation using classifier ensembles","volume":"166","author":"Vergara","year":"2012","journal-title":"Sens. Actuators B Chem."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1016\/j.jare.2012.05.007","article-title":"QRS detection using K-Nearest Neighbor algorithm (KNN) and evaluation on standard ECG databases","volume":"4","author":"Saini","year":"2013","journal-title":"J. Adv. Res."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/6\/1909\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:08:20Z","timestamp":1760195300000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/6\/1909"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,6,12]]},"references-count":33,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2018,6]]}},"alternative-id":["s18061909"],"URL":"https:\/\/doi.org\/10.3390\/s18061909","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,6,12]]}}}