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A database including 336 sets of engineering practical samples was established for rockburst prediction based on literature research. An improved salp swarm algorithm (ISSA) was adopted to optimize the support vector machine (SVM), and then an ISSA-SVM model was constructed for predicting the rockburst intensity grade and its effectiveness was also verified. Results show that this ISSA-SVA model for rockburst prediction can have accuracy up to 94.0%, much higher than other model, which can provide a certain scientific basis for rockburst prevention and control.

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采用文献调研法建立了1个包括336组工程实例样本的岩爆预测数据库，采用改进的樽海鞘算法（ISSA）优化支持向量机（SVM），构建了岩爆烈度等级预测模型（ISSA-SVM），并对其模型有效性进行了验证。结果表明，ISSA-SVM岩爆预测模型的预测准确率可达94.0%，相对于其他模型具有更高的准确性，可为岩爆防控提供一定的科学依据。

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田睿（1988—），男，内蒙古四子王旗人，博士，讲师，主要从事数据分析与挖掘、岩石力学与工程的研究工作。

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田睿（1988—），男，内蒙古四子王旗人，博士，讲师，主要从事数据分析与挖掘、岩石力学与工程的研究工作。

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