Research on gas monitoring and early warning system in coal mines based on quantum bee colony optimization algorithm

The gas monitoring and early warning system in coal mines is crucial for ensuring miners' safety and preventing accidents. This paper presents a novel coal mine gas monitoring and early warning system based on the quantum bee colony optimization algorithm, which aims to enhance the accuracy and responsiveness of the system. By integrating quantum computing with classic bee colony optimization techniques, the quantum bee colony optimization algorithm efficiently processes gas data, facilitating real-time monitoring and early warning. Simulation experiments validate that this algorithm outperforms traditional methods in predicting gas concentration and in the early warning model. The findings indicate that the quantum bee colony optimization algorithm not only improves the accuracy of gas monitoring in coal mines but also significantly reduces the false alarm rate, thereby enhancing the overall efficiency of coal mine safety management.