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In order to further improve the prediction accuracy of slope stability，a slope stability prediction model based on MISSA optimized SVM was proposed. Six representative indexes，including bulk density (γ)，cohesion (c)，internal friction angle (Ф)，slope angle (φf)，slope height (H) and pore pressure ratio (ru) were selected as the prediction indexes of the model. In response to the problems of slow convergence speed，low accuracy，and susceptibility to local optima in the sparrow optimization algorithm (SSA)，strategies such as one-dimensional composite chaotic mapping，SCA，Levy flight mechanism，and dynamic adjustment of step size factor are introduced for optimization and improvement. A slope stability prediction model based on MISSA-SVM was constructed. The MISSA-SVM model was applied to 9 groups of slope engineering examples，such as the Daxi landslide，for verification. The results show that the accuracy，precision，recall，F1 score，mean square error (MSE) and area under the curve (AUC) of the MISSA-SVM model reach 96.29%，92.3%，100%，0.96，0.016 and 0.967，respectively，which are better than the SSA-optimized SVM model and BP model，and the prediction results are completely consistent with the actual slope conditions，indicating that the MISSA-SVM model has strong generalization ability.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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