Automatic classification and permittivity estimation of organic solvents using a dielectric resonator sensor and machine learning techniques
| dc.contributor.author | Monteagudo Honrubia, Miguel | es-ES |
| dc.contributor.author | Herraiz Martínez, Francisco Javier | es-ES |
| dc.contributor.author | Matanza Domingo, Javier | es-ES |
| dc.date.accessioned | 2025-09-26T18:02:24Z | |
| dc.date.available | 2025-09-26T18:02:24Z | |
| dc.date.issued | 2022-12-31 | es_ES |
| dc.description | Capítulos en libros | es_ES |
| dc.description.abstract | This paper presents the application of a dielectric resonator sensor to characterize organic solvents. Two different acquisition systems were implemented to test the sensor and compare the results between a Vector Network Analyzer (VNA) and a low-cost portable electronic reader presented in this paper. Five dissolutions and air were measured within a permittivity range from 1 to 80. Principal Component Analysis (PCA) and Support Vector Machine (SVM) were used to perform automatic classification achieving an accuracy close to the 100 for both systems. | es-ES |
| dc.description.abstract | This paper presents the application of a dielectric resonator sensor to characterize organic solvents. Two different acquisition systems were implemented to test the sensor and compare the results between a Vector Network Analyzer (VNA) and a low-cost portable electronic reader presented in this paper. Five dissolutions and air were measured within a permittivity range from 1 to 80. Principal Component Analysis (PCA) and Support Vector Machine (SVM) were used to perform automatic classification achieving an accuracy close to the 100 for both systems. | en-GB |
| dc.description.version | info:eu-repo/semantics/publishedVersion | es_ES |
| dc.format.mimetype | application/pdf | es_ES |
| dc.identifier.uri | http://hdl.handle.net/11531/105369 | |
| dc.keywords | es-ES | |
| dc.keywords | en-GB | |
| dc.language.iso | en-GB | es_ES |
| dc.publisher | Universidad de Málaga; Union Radio-Scientifique Internationale (Málaga, España) | es_ES |
| dc.rights | es_ES | |
| dc.rights.accessRights | info:eu-repo/semantics/restrictedAccess | es_ES |
| dc.rights.uri | es_ES | |
| dc.source | Libro: XXXVII Simposio Nacional de la Unión Científica Internacional de Radio - URSI 2022, Página inicial: 1-4, Página final: | es_ES |
| dc.subject.other | Instituto de Investigación Tecnológica (IIT) | es_ES |
| dc.title | Automatic classification and permittivity estimation of organic solvents using a dielectric resonator sensor and machine learning techniques | es_ES |
| dc.type | info:eu-repo/semantics/bookPart | es_ES |
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