Signal Recognition Model of Ginseng Diseases and Insect Pests in Agricultural Internet of things
- DOI
- 10.2991/icmmct-18.2018.52How to use a DOI?
- Keywords
- Signal recognition model, ginseng diseases and pests, Agricultural Internet of things, catastrophe critical value, signal characteristics
- Abstract
In view of the relationship between diseases and insect pests in the growth process of ginseng, the safety of ginseng planting production and the key scientific problems of product quality and yield are solved, and the signal identification model of ginseng disease and insect pest is adopted to ensure the quality and safety of ginseng products and the increase of yield. Combined with the key technology of Agricultural Internet of things, a signal recognition model for diseases and pests of ginseng was constructed to realize the identification of pests and diseases in the process of ginseng planting. A signal recognition model for ginseng pests and diseases in Agricultural Internet of things is proposed, and the fuzzy clustering probability of signal characteristics is calculated to get the critical value of catastrophic anomalies. The simulation results show that the proposed model algorithm can obtain accurate data of ginseng disease and insect pests signal, the error after test is 0.00213, the correct rate of normal ginseng signal is 91.03%, and the correct rate of ginseng signal is 99.93%, which greatly improves the accuracy of the signal recognition model of ginseng disease and insect pests.
- Copyright
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Laiwu Yin AU - Shuyun Cai AU - Changcheng Li PY - 2018/06 DA - 2018/06 TI - Signal Recognition Model of Ginseng Diseases and Insect Pests in Agricultural Internet of things BT - Proceedings of the 2018 6th International Conference on Machinery, Materials and Computing Technology (ICMMCT 2018) PB - Atlantis Press SP - 257 EP - 262 SN - 2352-5401 UR - https://doi.org/10.2991/icmmct-18.2018.52 DO - 10.2991/icmmct-18.2018.52 ID - Yin2018/06 ER -