针对混沌理论中基于最大Lyapunov指数预测瓦斯浓度过程中符号不确定的问题，在简化的C-C方法重构瓦斯浓度时间序列的相空间和Wolf方法计算最大Lyapunov指数谱的基础上，引入加权局域的思想优化瓦斯浓度预测模型。仿真结果表明：加权局域点个数为5时，改进预测算法最优，且比传统Lyapunov指数预测更精确。%Based on chaos theory, the symbol is uncertain when using the largest Lyapunov exponent to predict the gas concentra-tion.In order to solve this problem, the simplified C-C method is used to reconstruct the sequence of gas concentration and the Wolf method is used to calculate the largest Lyapunov exponent. Then uses the weighted local thought to establish the gas concen-tration predict model.The emulation experiment shows the prediction algorithm is optimal when the weighted number is 5, and more accurate than the traditional Lyapunov exponent prediction.
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