针对燃煤机组锅炉主再热汽温控制中存在的滞后性、多变量耦合及动态工况适应难题,文章提出一种融合数字孪生技术与最小二乘支持向量机(Least Squares Support Vector Machine,LS-SVM)的汽温寻优方法。通过构建锅炉三维数字孪生模型实现...针对燃煤机组锅炉主再热汽温控制中存在的滞后性、多变量耦合及动态工况适应难题,文章提出一种融合数字孪生技术与最小二乘支持向量机(Least Squares Support Vector Machine,LS-SVM)的汽温寻优方法。通过构建锅炉三维数字孪生模型实现设备状态实时映射,结合LS-SVM建立多变量动态预测模型,并引入多目标微分进化算法(MODE)进行参数优化。实际应用表明,该方法使主汽温波动范围从±7℃缩小至±2.5℃,再热汽温预测误差稳定在±1.5℃以内,年节约燃煤成本超400万元,为火电机组深度调峰与能效提升提供技术支撑。展开更多
针对现有电力系统短期负荷预测精度低、数据处理量大、易受输入变量的影响等问题,提出了一种将离散Fréchet距离与LS-SVM相结合的短期负荷预测方法。分析总结了East-Slovakia Power Distribution Company提供的历年负荷数据,结合该...针对现有电力系统短期负荷预测精度低、数据处理量大、易受输入变量的影响等问题,提出了一种将离散Fréchet距离与LS-SVM相结合的短期负荷预测方法。分析总结了East-Slovakia Power Distribution Company提供的历年负荷数据,结合该地区的用电规律,通过引入离散Fréchet距离,建立离散曲线相似性的数学模型,选取出与基准曲线形状相似的相似日,利用相似日负荷数据对LS-SVM预测模型进行训练。经过仿真验证,并与标准LS-SVM模型得到的结果对比,所提预测方法明显提高了预测精度。展开更多
利用最小二乘支持向量机(Least Squares Support Vector Machines,LS-SVM),设计了一个电液位置伺服闭环控制系统的多故障诊断系统。利用系统的可测参量,建立了基于LS-SVM的电液位置伺服系统的全局故障检测模型和局部故障检测模型。在仿...利用最小二乘支持向量机(Least Squares Support Vector Machines,LS-SVM),设计了一个电液位置伺服闭环控制系统的多故障诊断系统。利用系统的可测参量,建立了基于LS-SVM的电液位置伺服系统的全局故障检测模型和局部故障检测模型。在仿真过程中发现,此方法的诊断准确度高,适用于闭环系统的单故障及多故障的检测及定位,仿真结果验证了该方法的有效性。展开更多
In this paper, a new method based on LS-SVM (Least Squares Support Vector Machines) is presented to deal with credit assessment in commercial banks for solving the problem of inadequate samples of the financial data,w...In this paper, a new method based on LS-SVM (Least Squares Support Vector Machines) is presented to deal with credit assessment in commercial banks for solving the problem of inadequate samples of the financial data,which usually happended in most banks in China.On the basis of SLT(Statistical Learning Theory),this approach with methodology of SRM (Structural Risk Minimization)will overcome the shortcomings of traditional credit assessment models,such as over fitting and local optimization,and,by using kernel functions in model,it will effectively solve the problems of linear inseparability and selecting parameters of model.The approach has some good properties including a generalization ability and global optimization in terms of sample processing.It is a new way for the credit assessment on the condition of small samples from bank data.The feasibility,effectiveness and practicability of presented approach was verified by experiments.展开更多
文摘针对燃煤机组锅炉主再热汽温控制中存在的滞后性、多变量耦合及动态工况适应难题,文章提出一种融合数字孪生技术与最小二乘支持向量机(Least Squares Support Vector Machine,LS-SVM)的汽温寻优方法。通过构建锅炉三维数字孪生模型实现设备状态实时映射,结合LS-SVM建立多变量动态预测模型,并引入多目标微分进化算法(MODE)进行参数优化。实际应用表明,该方法使主汽温波动范围从±7℃缩小至±2.5℃,再热汽温预测误差稳定在±1.5℃以内,年节约燃煤成本超400万元,为火电机组深度调峰与能效提升提供技术支撑。
文摘针对现有电力系统短期负荷预测精度低、数据处理量大、易受输入变量的影响等问题,提出了一种将离散Fréchet距离与LS-SVM相结合的短期负荷预测方法。分析总结了East-Slovakia Power Distribution Company提供的历年负荷数据,结合该地区的用电规律,通过引入离散Fréchet距离,建立离散曲线相似性的数学模型,选取出与基准曲线形状相似的相似日,利用相似日负荷数据对LS-SVM预测模型进行训练。经过仿真验证,并与标准LS-SVM模型得到的结果对比,所提预测方法明显提高了预测精度。
文摘利用最小二乘支持向量机(Least Squares Support Vector Machines,LS-SVM),设计了一个电液位置伺服闭环控制系统的多故障诊断系统。利用系统的可测参量,建立了基于LS-SVM的电液位置伺服系统的全局故障检测模型和局部故障检测模型。在仿真过程中发现,此方法的诊断准确度高,适用于闭环系统的单故障及多故障的检测及定位,仿真结果验证了该方法的有效性。
文摘In this paper, a new method based on LS-SVM (Least Squares Support Vector Machines) is presented to deal with credit assessment in commercial banks for solving the problem of inadequate samples of the financial data,which usually happended in most banks in China.On the basis of SLT(Statistical Learning Theory),this approach with methodology of SRM (Structural Risk Minimization)will overcome the shortcomings of traditional credit assessment models,such as over fitting and local optimization,and,by using kernel functions in model,it will effectively solve the problems of linear inseparability and selecting parameters of model.The approach has some good properties including a generalization ability and global optimization in terms of sample processing.It is a new way for the credit assessment on the condition of small samples from bank data.The feasibility,effectiveness and practicability of presented approach was verified by experiments.
