# Research on Plant Disease and Pest Diagnosis Model Based on Generalized Stochastic Petri Net
## 4 Simulation Analysis
### Stimulation Analysis of the Pest and Disease Diagnosis Model
#### 4.2.2 Disease Judgment Stage
For example, when \(\lambda_{11}=1.8\) and \(\lambda_{9}=2.4\), \(\mathrm{P}(\mathrm{M}_{12})=0.0231\). This indicates that under this infection rate combination, the probability of meeting the treatment criteria is 2.31%. The system needs to activate the early warning mechanism and promptly implement corresponding control measures. Compared to the \(\lambda_{9}\), \(\lambda_{10}\) combination and the \(\lambda_{10}\), \(\lambda_{11}\) combination, the \(\lambda_{11}\), \(\lambda_{9}\) rate combination has an intermediate impact on the probability of meeting the treatment criteria. This indicates that, although the individual effect of mild infection is relatively small, its combined impact with severe infection remains significant. Therefore, in the pest and disease control process, it is essential to consider the combined effects of different infection stages and develop multi-level control strategies to ensure timely and effective management of disease progression. Through the comparative analysis of the different infection rate combinations, the key impacts of different infection stages on pest and disease control can be identified. To further understand the complex spread mechanisms of plant pests and diseases, and to develop more effective control strategies in practical applications, the interactions between the mild infection rate, moderate infection rate, and severe infection rate will continue to be explored in order to establish graded early warning and control strategies. Figure 7: Relationship between moderate infection rate, severe infection rate, and probability of meeting treatment criteria. Three different early warning activation thresholds are set to measure the severity of pest and disease occurrence and trigger the corresponding control measures. The specific definitions are as follows: When the probability of pest and disease occurrence reaches 0.005, the system activates the blue alert. This is applicable when pests or diseases have just started to appear or have a low level of spread, and the main goal is early detection and prevention to avoid further spread of the condition. When the probability of pest and disease occurrence reaches 0.01, the system activates the yellow alert. This applies when the pest and disease spread is more significant but not yet severe, requiring more active control measures to manage the disease progression. When the probability of pest and disease occurrence reaches 0.015, the system activates the red alert. This applies when the pest and disease spread is rapid and severe, requiring immediate and strong control measures to prevent widespread economic losses and plant death. As shown in Figure 9, when \(\lambda_{9}=1.15,\lambda_{10}=0.13,\lambda_{11}=0.95\), the system reaches the blue alert critical surface, indicating the need for attention and early control measures. When \(\lambda_{9}=1.17,\lambda_{10}=0.37,\lambda_{11}=1.81\), the system reaches the yellow alert critical surface, suggesting the need for more active control measures to prevent further deterioration of the condition. When \(\lambda_{9}=1.59,\lambda_{10}=0.88,\lambda_{11}=1.84\), the system reaches the red alert critical surface, requiring immediate and strong control measures to prevent widespread economic losses. Figure 8: Relationship between severe infection rate, mild infection rate, and probability of meeting treatment criteria. Figure 9: Critical surface of plant pest and disease early warning.