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Landslide susceptibility modeling based on ANFIS with teaching-learning-based optimization and Satin bowerbird optimizer 总被引:1,自引:0,他引:1
As threats of landslide hazards have become gradually more severe in recent decades,studies on landslide prevention and mitigation have attracted widespread attention in relevant domains.A hot research topic has been the ability to predict landslide susceptibility,which can be used to design schemes of land exploitation and urban development in mountainous areas.In this study,the teaching-learning-based optimization(TLBO)and satin bowerbird optimizer(SBO)algorithms were applied to optimize the adaptive neuro-fuzzy inference system(ANFIS)model for landslide susceptibility mapping.In the study area,152 landslides were identified and randomly divided into two groups as training(70%)and validation(30%)dataset.Additionally,a total of fifteen landslide influencing factors were selected.The relative importance and weights of various influencing factors were determined using the step-wise weight assessment ratio analysis(SWARA)method.Finally,the comprehensive performance of the two models was validated and compared using various indexes,such as the root mean square error(RMSE),processing time,convergence,and area under receiver operating characteristic curves(AUROC).The results demonstrated that the AUROC values of the ANFIS,ANFIS-TLBO and ANFIS-SBO models with the training data were 0.808,0.785 and 0.755,respectively.In terms of the validation dataset,the ANFISSBO model exhibited a higher AUROC value of 0.781,while the AUROC value of the ANFIS-TLBO and ANFIS models were 0.749 and 0.681,respectively.Moreover,the ANFIS-SBO model showed lower RMSE values for the validation dataset,indicating that the SBO algorithm had a better optimization capability.Meanwhile,the processing time and convergence of the ANFIS-SBO model were far superior to those of the ANFIS-TLBO model.Therefore,both the ensemble models proposed in this paper can generate adequate results,and the ANFIS-SBO model is recommended as the more suitable model for landslide susceptibility assessment in the study area considered due to its excellent accuracy and efficiency. 相似文献
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基于分布式检测与决策融合的海底油气管线检漏 总被引:3,自引:0,他引:3
利用多传感器的信息融合思想,提出分布式检测与决策融合方法进行长距离海底管线泄漏监测。试验水管和天然气/凝析油管线现场数据分析表明此算法不仅降低了误报警概率,且对流体在输送过程中动态变化具有稳健性。 相似文献
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大深度载人潜水器低速大漂角模糊滑模航向控制研究 总被引:1,自引:0,他引:1
通过模型试验测量大深度载人潜水器低速大漂角运动时所受到的非线性水动力。基于一种新的模糊滑模控制策略,为潜水器设计了鲁棒航向控制器。在不同的漂角子区间内分别设计局部镇定的滑模控制器,然后通过Takagi-Sugeno模糊推理系统将它们光滑连接,得到模糊滑模控制。仿真计算结果充分显示了该控制策略的有效性。 相似文献
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敦煌-格尔木铁路沿线地形复杂、起沙因素多变、沙源丰富,沙害问题日益严重。目前对其风沙活动规律还未有研究,不利于防沙工作的开展。为此,通过对自北向南的5个观测点(S1、S2、S3、S4、S5)风速和风向的观测、计算和分析,利用平均风速、起沙风况及输沙势对敦格铁路沿线的风动力环境特征进行研究。结果表明:S5、S4和S3的风况对铁路风沙灾害防治意义较大。S5年平均风速、起沙风频率和输沙势最大,春季风沙活动最为强烈,且风向单一、风力强劲,风沙运动方向基本与铁路垂直,沙粒易在铁路附近堆积。S4夏季风沙活动最为强烈;S3春季风沙活动最为强烈,且风向单一,S4和S3的风沙运动方向与铁路夹角小于90°,附近沙源广阔,铁路易受风沙侵蚀,阻碍交通运营。 相似文献
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Feiyu Liu Wenqing Wu Jun Wang Jun Hai Yuanqiang Cai 《Marine Georesources & Geotechnology》2020,38(2):164-173
AbstractTo achieve the rapid dewatering of dredged sludge, the flocculation–vacuum-preloading method was tested indoors. In this study, the optimal mixing ratio of six flocculants was determined through the settling column test, and then the proposed method was tested. The water drainage and settlement were monitored during the test, while the soil moisture content and shear strength were measured after the test. The results show that all the flocculants had an optimal mixing ratio, and the addition of 0.8% FeCl3 or 0.08% anionic polyacrylamide (APAM) in the sludge can better accelerate solid–liquid separation of the sludge. After the test, the water content in the sludge decreased from 140% to 60%. Compared with general vacuum preloading, the use of the proposed method increased the water drainage by 46.5% and 56.8% and decreased the soil volumes by 60.5% and 82.4% for FeCl3 and APAM, respectively. Moreover, the corresponding shear strength was increased from 10 to 14 and 17?kPa. In addition, the use of APAM increased the solidification rate of heavy metals in the sludge to more than 80%, effectively inhibiting the migration of heavy metals. 相似文献