目前导水裂隙带发育高度的研究大多针对的是单一煤层开采导水裂隙带高度，而对于巨厚煤层开采覆岩导水裂隙带发育高度预测研究较少。基于新疆侏罗系煤田巨厚煤层地质条件，选取新疆准南煤田硫磺沟煤矿（9−15）08典型工作面参数，通过数值模拟和分形几何理论分析，定量评价巨厚煤层在综放分层开采条件下覆岩裂隙场的发育特征和演化规律，并构建了基于粒子群优化支持向量机回归（PSO−SVR）的巨厚煤层分层开采导水裂隙带高度预测模型。研究结果表明：① 巨厚煤层分层开采时，老顶范围内坚硬岩层和亚关键层呈铰接结构，整体上覆岩变形破坏呈拱式结构。② 受采动影响，顶板覆岩破断垮落，横向裂隙不断发育生成，且垂向裂隙向上发育，导水裂隙带持续上升，分形维数快速上升。而随着工作面的持续推进，上覆岩层裂隙中横向裂隙被上覆岩层压实，裂隙开度降低，分形维数逐渐降低。③ 分层开采时裂隙分形维数总体呈现为升维、降维、稳定和波动4个阶段。④ 选用平均绝对误差（MAE）、平均偏差（MBE）和相关指数R²等指标对PSO−SVR模型进行了评估，其相关指数R²＞0.90，MAE＜6.5 m，−0.5 m＜MBE＜0.5 m，表明建立的PSO−SVR模型能够用于分层综放开采导水裂隙带高度预测。⑤ 将9−15（08）工作面数据代入PSO−SVR模型中，预测值与实测值绝对误差为12.52 m，相对误差为4.86%，表明PSO−SVR能够有效、准确地进行巨厚煤层开采导水裂隙带高度预测。

Current research on the developing heights of water-conducting fracture zones mainly focuses on the heights of water-conducting fracture zones in single coal seam mining, while research on the prediction of the developing heights of water-conducting fracture zones in extremely thick coal seams mining is relatively scarce. Based on the geological conditions of the extremely thick coal seams in the Jurassic coalfields of Xinjiang, this research selected the parameters of the typical working face 9-15 (08) in the Liuhuanggou Coal Mine of the Zhunnan Coalfield in Xinjiang, quantitatively evaluated the development characteristics and evolution patterns of the overlying rock fracture fields under layered full-mechanized mining of extremely thick coal seams through numerical simulations and fractal geometry theory analysis. A prediction model was developed for the heights of water-conducting fracture zones in layered mining of extremely thick coal seams based on particle swarm optimization support vector machine regression (PSO-SVR). The research results showed that: ① During layered mining of extremely thick coal seams, the hard rock strata and inferior key strata within the capping range exhibited a hinged structure, and the overall deformation and failure of the overlying rocks presented an arched structure. ② The impact of mining activities caused the roof overlying rocks to fracture and collapse, with horizontal fractures continuously developing and vertical fractures extending upwards. The water-conducting fracture zones rose continuously, and the fractal dimension increased rapidly. As the working face continued to advance, the horizontal fractures within the overlying rock layers were compacted by the layer above, the fracture aperture decreased, and the fractal dimension gradually reduced. ③ During layered mining, the fractal dimension of fractures generally exhibited four stages: ascending dimension stage, dimension reduction stage, stationary stage, and fluctuating stage. ④ The PSO-SVR model was evaluated using indicators including mean absolute error (MAE), mean bias error (MBE), and correlation index R². The model showed that correlation index R²＞0.90, MAE＜6.5 m, −0.5 m＜MBE＜0.5 m, indicating that the PSO-SVR model was capable of predicting the heights of water-conducting fracture zones in layered full-mechanized mining. ⑤ By substituting the data from the working face 9-15(08) into the PSO-SVR model, the absolute error between the predicted and observed values was 12.52 m, and the relative error was 4.86%, indicating that the PSO-SVR model could effectively and accurately predict the heights of the water-conducting fracture zones in extremely thick coal seams mining.