ArticleSensors (Basel, Switzerland)2018
Comparison of SVM, RF and ELM on an Electronic Nose for the Intelligent Evaluation of Paraffin Samples.
Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Label-free refractive index mapping of human sperm cells.Biomedical optics express · 2025Article
- Development of a Novel HS-GC/MS Method Using the Total Ion Spectra Combined with Machine Learning for the Intelligent and Automatic Evaluation of Food-Grade Paraffin Wax Odor Level.Foods (Basel, Switzerland) · 2024Article
- Analysis of the Response Signals of an Electronic Nose Sensor for Differentiation betweenSensors (Basel, Switzerland) · 2023Article
- Application of Machine Learning Methods for an Analysis of E-Nose Multidimensional Signals in Wastewater Treatment.Sensors (Basel, Switzerland) · 2023Article
- Rapid Detection and Quantification of Adulterants in Fruit Juices Using Machine Learning Tools and Spectroscopy Data.Sensors (Basel, Switzerland) · 2022Article
- Kynurenine and Hemoglobin as Sex-Specific Variables in COVID-19 Patients: A Machine Learning and Genetic Algorithms Approach.Diagnostics (Basel, Switzerland) · 2021Article
- Application of Machine Learning for Fenceline Monitoring of Odor Classes and Concentrations at a Wastewater Treatment Plant.Sensors (Basel, Switzerland) · 2021Article
- Five Typical Stenches Detection Using an Electronic Nose.Sensors (Basel, Switzerland) · 2020Article
- Quantitative and Qualitative Analysis of Multicomponent Gas Using Sensor Array.Sensors (Basel, Switzerland) · 2019Article
- Support Vector Machine Optimized by Genetic Algorithm for Data Analysis of Near-Infrared Spectroscopy Sensors.Sensors (Basel, Switzerland) · 2018Article
- Odor Discrimination by Similarity Measures of Abstract Odor Factor Maps from Electronic Noses.Sensors (Basel, Switzerland) · 2018Article
- Force Trends and Pulsatility for Catheter Contact Identification in Intracardiac Electrograms during Arrhythmia Ablation.Sensors (Basel, Switzerland) · 2018Article
- Gas Array Sensors based on Electronic Nose for Detection of Tuna (Journal of medical signals and sensorsArticle
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Paraffin odor intensity is an important quality indicator when a paraffin inspection is performed. Currently, paraffin odor level assessment is mainly dependent on an artificial sensory evaluation. In this paper, we developed a paraffin odor analysis system to classify and grade four kinds of paraffin samples. The original feature set was optimized using Principal Component Analysis (PCA) and Partial Least Squares (PLS). Support Vector Machine (SVM), Random Forest (RF), and Extreme Learning Machine (ELM) were applied to three different feature data sets for classification and level assessment of paraffin. For classification, the model based on SVM, with an accuracy rate of 100%, was superior to that based on RF, with an accuracy rate of 98.33-100%, and ELM, with an accuracy rate of 98.01-100%. For level assessment, the R² related to the training set was above 0.97 and the R² related to the test set was above 0.87. Through comprehensive comparison, the generalization of the model based on ELM was superior to those based on SVM and RF. The scoring errors for the three models were 0.0016-0.3494, lower than the error of 0.5-1.0 measured by industry standard experts, meaning these methods have a higher prediction accuracy for scoring paraffin level.
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