ArticleSensors (Basel, Switzerland)2018
Determination of Odour Interactions in Gaseous Mixtures Using Electronic Nose Methods with Artificial Neural Networks.
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 18 papers.
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Who cites it
18 citing papers in PubMed, 61 citations in OpenAlex.
- Odor prediction of whiskies based on their molecular composition.Communications chemistry · 2024Article
- Performance of a Novel Electronic Nose for the Detection of Volatile Organic Compounds Relating to Starvation or Human Decomposition Post-Mass Disaster.Sensors (Basel, Switzerland) · 2024Article
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- Malodour classification with low-cost flexible electronics.Nature communications · 2023Article
- Machine Learning Enhances the Performance of Bioreceptor-Free Biosensors.Sensors (Basel, Switzerland) · 2021Review
- A Multi-Sensor System for Sea Water Iodide Monitoring and Seafood Quality Assurance: Proof-of-Concept Study.Sensors (Basel, Switzerland) · 2021Article
- DeepGRAI (Deep Gray Rating via Artificial Intelligence): Fast, feasible, and clinically relevant thalamic atrophy measurement on clinical quality T2-FLAIR MRI in multiple sclerosis.NeuroImage. Clinical · 2021Article
- Instrumental Odour Monitoring System Classification Performance Optimization by Analysis of Different Pattern-Recognition and Feature Extraction Techniques.Sensors (Basel, Switzerland) · 2020Article
- Characterization and Neural Modeling of a Microwave Gas Sensor for Oxygen Detection Aimed at Healthcare Applications.Sensors (Basel, Switzerland) · 2020Article
- Integrated model for estimating odor emissions from civil wastewater treatment plants.Environmental science and pollution research international · 2020Article
- Review on Smart Gas Sensing Technology.Sensors (Basel, Switzerland) · 2019Review
- Determination of Odor Intensity of Binary Gas Mixtures Using Perceptual Models and an Electronic Nose Combined with Fuzzy Logic.Sensors (Basel, Switzerland) · 2019Article
- Mixed Natural Gas Online Recognition Device Based on a Neural Network Algorithm Implemented by a FPGA.Sensors (Basel, Switzerland) · 2019Article
- Monitoring of Cell Concentration duringSensors (Basel, Switzerland) · 2019Article
- A New Method of Mixed Gas Identification Based on a Convolutional Neural Network for Time Series Classification.Sensors (Basel, Switzerland) · 2019Article
- Cheeses Made from Raw and Pasteurized Cow's Milk Analysed by an Electronic Nose and an Electronic Tongue.Sensors (Basel, Switzerland) · 2018Article
- An Electronic Nose Based Method for the Discrimination of Weathered Petroleum-Derived Products.Sensors (Basel, Switzerland) · 2018Article
- Rapid assessment of the authenticity of limequat fruit using the electronic nose and gas chromatography coupled with mass spectrometry.Monatshefte fur chemie · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper presents application of an electronic nose prototype comprised of eight sensors, five TGS-type sensors, two electrochemical sensors and one PID-type sensor, to identify odour interaction phenomenon in two-, three-, four- and five-component odorous mixtures. Typical chemical compounds, such as toluene, acetone, triethylamine, α-pinene and n-butanol, present near municipal landfills and sewage treatment plants were subjected to investigation. Evaluation of predicted odour intensity and hedonic tone was performed with selected artificial neural network structures with the activation functions tanh and Leaky rectified linear units (Leaky ReLUs) with the parameter a = 0.03 . Correctness of identification of odour interactions in the odorous mixtures was determined based on the results obtained with the electronic nose instrument and non-linear data analysis. This value (average) was at the level of 88% in the case of odour intensity, whereas the average was at the level of 74% in the case of hedonic tone. In both cases, correctness of identification depended on the number of components present in the odorous mixture.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.