...提出一种基于经验模式分解(empirical mode decomposition,EMD)近似熵和最小二乘支持向量机(least square support vector machine,LS-SVM)的机械故障诊断新方法。
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实现了基于数据挖掘理论和最小二乘支持向量机短时预测的多接口远程智能供水监管系统。
A short-term prediction system based on data mining preparation and least squares support vector machine was presented for a multi-port remote monitoring and management system.
提出了基于粒子群算法(PSO)和最小二乘支持向量机(LSSVM)的边坡稳定性评价方法。
A slope stability evaluation method based on particle swarm optimization (PSO) and least square support vector machine (LSSVM) is proposed.
现有最小二乘支持向量机回归的训练和模型输出的计算需要较长的时间，不适合在线实时训练。
Least square support vector machines regression without sparsity needs longer training time currently, and is not adapted to online real-time training.
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