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机译:采用GWO优化的支持向量机以预测土壤液化
Key Laboratory of Ministry of Education for Geomechanics and Embankment Engineering and College of Civil and Transportation Engineering Hohai University Nanjing 210098 China;
College of Civil Engineering University of Science and Technology Liaoning Anshan 114053 China;
Key Laboratory of Geotechnical and Underground Engineering of Ministry of Education and Department of Geotechnical Engineering Tongji University Shanghai 200092 China;
Key Laboratory of Geotechnical and Underground Engineering of Ministry of Education and Department of Geotechnical Engineering Tongji University Shanghai 200092 China;
Soil liquefaction; Prediction model; Support vector machine; Gray wolf optimization; Shear wave velocity;
机译:使用混合优化算法和模糊支持向量机改进土壤液化的预测
机译:基于遗传算法的支持向量机在土壤液化预测中的应用
机译:用混合载体方法预测非粘性路基土壤和未结合亚基石材料的弹性模量及碰撞体优化算法
机译:基于最小二乘的酸性气体脱硫装置优化—支持向量机模型和灰狼优化器
机译:高山亚洲积雪地形对被动微波亮度温度的支持向量机预测的敏感性分析
机译:基于支持向量机的石膏复垦土壤离子迁移的模拟与预测。
机译:优化支持向量机预测土壤物理性质
机译:通过增量近似最近支持向量快速查询优化的内核机器分类