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Signal Recognition Model of Ginseng Diseases and Insect Pests in Agricultural Internet of things

机译:物理互联网人参疾病与虫害的信号识别模型

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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.
机译:鉴于人参生长过程中疾病和虫害的关系,解决了人参种植生产的安全和产品质量和产量的关键科学问题,采用了人参疾病和虫害的信号识别模型确保人参产品的质量和安全和产量的增加。结合农业互联网的关键技术,构建了人参疾病和害虫的信号识别模型,以实现人参种植过程中害虫和疾病的鉴定。提出了一种用于农业互联网的人参害虫和疾病的信号识别模型,并计算了信号特性的模糊聚类概率,得到了灾难性异常的临界价值。仿真结果表明,该拟议的模型算法可以获得人参疾病和昆虫害虫信号的准确数据,试验后的误差为0.00213,正常人参信号的正确速率为91.03%,人参信号的正确速率为99.93%,大大提高了人参疾病和虫害的信号识别模型的准确性。

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