Abstract
The odor information of living hairy crab was collected by self-made electronic nose system. The dimension of multi-dimensional characteristic response of hairy crab samples was reduced by popular learning algorithm, and the low-dimensional feature vector of samples was extracted. Then, the freshness of hairy crab was identified by back-propagation neural network, and compared with the physical and chemical index volatile basic nitrogen. The results show that the accuracy of the algorithm can reach 98.1%, and the results based on the electronic nose technology and the physical and chemical indicators are basically the same. Therefore, the non-destructive identification method based on electronic nose technology is feasible.
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Fan, Z., Wang, Y. (2021). General Freshness Recognition Method Based on Electronic Nose and Improved Unsupervised Signature Projection Algorithm. In: Abawajy, J., Xu, Z., Atiquzzaman, M., Zhang, X. (eds) 2021 International Conference on Applications and Techniques in Cyber Intelligence. ATCI 2021. Advances in Intelligent Systems and Computing, vol 1398. Springer, Cham. https://doi.org/10.1007/978-3-030-79200-8_106
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DOI: https://doi.org/10.1007/978-3-030-79200-8_106
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