Full
Outline
In order to improve the filling efficiency and realize the continuous and stable desanding of the tailings storage thickener, combined with the actual situation of the mine and the test results of static and dynamic flocculation and sedimentation, the particle swarm optimization (PSO) algorithm was used to optimize the support vector machine (SVM) regression analysis method. The prediction model of desanding stability was established, and the prediction model was updated by the hybrid point addition method. The optimal parameters were determined by the optimization algorithm to realize the prediction of desanding stability of the tailings storage thickener. Taking Dongxinzhuang Iron Mine as an example, the optimal scheme of thickener structure parameters and desanding parameters based on PSO-SVM was completed and verified by industrial tests. The results show that the mud layer height and the combined effect of mud layer height, sand concentration and thickening time have the greatest influence on the stability of desanding. The PSO-SVM prediction model has a good accuracy in predicting the desanding stability, with a relative error of 1.36%. The research results can provide a theoretical basis for the selection of thickener shape parameters and desanding parameters, and can effectively improve the desanding stability of thickener.
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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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