Visual Analysis of Odor Interaction Based on Support Vector Regression Method.

ABSTRACT: The complex odor interaction between odorants makes it difficult to predict the odor intensity of their mixtures. The analysis method is currently one of the factors limiting our understanding of the odor interaction laws. We used a support vector regression algorithm to establish odor intensity prediction models for binary esters, aldehydes, and aromatic hydrocarbon mixtures, respectively. The prediction accuracy to both training samples and test samples demonstrated the high prediction capacity of the support vector regression model. Then the optimized model was used to generate extra odor data by predicting the odor intensity of more simulated samples with various mixing ratios and concentration levels. Based on these olfactory measured and model predicted data, the odor interaction was

SUBMITTER: Yan L 

PROVIDER: S-EPMC7146738 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature