## 4 Result and Discussion
### Stability Analysis
Inference 6: When \(HI<0\) and \(ST<0\), if \(H\) and \(S\) are of different signs, all points are saddle points and there is no evolutionary stable strategy for the system. By analyzing the 16 scenarios in the chart, this paper finds that when \(H>0\), \(I>0\), \(S>0\), and \(T>0\) (i.e., the evolutionary stability of the system behavior is the strongest when the value perception return bias is convergent and positive), the entire evolutionary game reaches the best equilibrium state. At this time, the value perception of coal mine enterprises fully implementing intelligent construction behavior and the value perception of local government strictly supervising behavior occupy a rational dominant position. This means that \(p=1\) when coal mine enterprises choose to fully implement the intelligent construction strategy of a coal mine and \(q=1\) when local government chooses to strictly supervise coal mine enterprises. In this case, the article has the following inferences. Inference 7: When \(H>0\), i.e., \(V(R_{1}+R_{2})+C(m_{2}+F_{1}+\alpha_{2}\omega(p_{0})L)>V(R_{1})\). Since both \(V(x)\) and \(C(x)\) are increasing functions, then the corresponding variable satisfies \(R_{2}>0\), \(m_{2}+F_{1}+\alpha_{2}\omega(p_{0})L>0\). This implies that, in the event that coal mining enterprises are obliged to implement intelligent construction, it is imperative that they are able to guarantee that such enterprises will receive supplementary rewards and earnings \(R_{2}\) resulting from intelligent construction. Inference 8: When \(I>0\), i.e., \(V(R_{1}+R_{2})+C(m_{2}+\omega(p_{0})L)>V(R_{1})+C(m_{0}+m_{1}+t\alpha_{1} \omega(p_{0})L)\). This implies that the corresponding variable satisfies \(m_{2}+\omega(p_{0})L>m_{0}+m_{1}+t\alpha_{1}\omega(p_{0})L\). It can be seen that the greater the psychological cost \(m_{2}\), the higher the degree to which coal mining enterprises fully implement intelligent construction. When the unimplemented psychological cost \(m_{2}\) is higher than the implemented labor cost \(m_{0}\) and mental cost \(m_{1}\), it is more beneficial for coal mining enterprises to achieve an evolutionary stability strategy. In addition, the accident risk transfer coefficient \(t\) and the safety risk coefficient \(\alpha_{1}\) also have a significant impact on this condition. The appropriate reduction, within a limited range, can promote the evolutionary game between the two sides to reach a balanced state. Inference 9: When \(S>0\), i.e., \(C(g_{2}+F_{2}+\alpha_{1}\omega(p_{0})L)>C(g_{0}+g_{1})\), the corresponding variable satisfies \(g_{2}+F_{2}+\alpha_{1}\omega(p_{0})L>g_{0}+g_{1}\) at this time. The sum of the psychological cost \(g_{2}\) of the local government department's deregulation, the penalty \(F_{2}\), and the accident risk cost \(\alpha_{1}\omega(p_{0})L\) should be greater than the labor cost \(g_{0}\) and the mental cost \(g_{1}\) of its strict regulation. Inference 10: When \(T>0\), i.e., \(V(B_{1}+\beta F_{1})+C(g_{2}+F_{2}+\omega(p_{0})L)>V(B_{1}+\omega(p_{1})G)+C(g_ {0}+g_{1}+t\alpha_{2}\omega(p_{0})L)\), the corresponding variable satisfies \(\beta F_{1}>\omega(p_{1})G_{\beta 2}+F_{2}+\omega(p_{0})L>g_{0}+g_{1}+t\alpha_{2} \omega(p_{0})L\) at this time. The performance reward \(\beta F_{1}\), obtained by the local government by investigating and handling the non-implementation of intelligent construction coal mines, should be as high as possible, in relation to the benefit \(\omega(p_{1})G\) obtained from the coal mine when it relaxed regulations. The above inference does not contain any cases that cannot be calculated or derived. This situation indicates that the players' utility can be modeled using a value function that reflects reference dependence and loss aversion, consistent with prospect theory. Specifically, the results show that both the coal mining enterprise and the government mechanism can adopt the value function as their income target, and with all parameters being significantly greater than zero and fixed, this is largely supported by the results.