为实现钢铁件渗碳层深度的在线电磁无损检测,提出在线最小二乘支持向量机(Online Least Square Support Vector Machine,Online LS-SVM)的建模方法。Online LS-SVM是以增量学习训练SVM,以减量学习减少样本数,实现小样本估计的训练方法...为实现钢铁件渗碳层深度的在线电磁无损检测,提出在线最小二乘支持向量机(Online Least Square Support Vector Machine,Online LS-SVM)的建模方法。Online LS-SVM是以增量学习训练SVM,以减量学习减少样本数,实现小样本估计的训练方法。实验结果表明,Online LS-SVM不仅能实现钢铁件渗碳层深度的在线电磁无损检测,而且具有学习速度快、泛化性能好和对样本依赖程度低的优点。展开更多
为了实现钢铁件淬火硬度的在线电磁无损检测,提出了在线最小二乘支持向量机(online least square support vector machine)的建模方法。Online LS-SVM是以增量学习训练SVM,以减量学习减少样本数,实现小样本估计的训练方法。实验结果表明...为了实现钢铁件淬火硬度的在线电磁无损检测,提出了在线最小二乘支持向量机(online least square support vector machine)的建模方法。Online LS-SVM是以增量学习训练SVM,以减量学习减少样本数,实现小样本估计的训练方法。实验结果表明,Online LS-SVM不仅能实现钢铁件淬火硬度的在线电磁无损检测,而且具有学习速度快,泛化性能好,对样本依赖程度低的优点。展开更多
In recent years, advanced control technologies have been used for the optimum control of a cold storage. But there are still a lot of shortcomings. One of the main problems is that the traditional methods can't re...In recent years, advanced control technologies have been used for the optimum control of a cold storage. But there are still a lot of shortcomings. One of the main problems is that the traditional methods can't realize the on-line predictive optimum control of a refrigerating system with simple and valid algorithms. An RBF neural network has a strong ability in nonlinear mapping, a good interpolating value performance, and a higher training speed. Thus a two-stage RBF neural network is proposed in this paper. Combining the measured values with the predicted values, the two-stage RBF neural network is used for the on-line predictive optimum control of the cold storage temperature. The application results of the new methods show a great success.展开更多
文摘为实现钢铁件渗碳层深度的在线电磁无损检测,提出在线最小二乘支持向量机(Online Least Square Support Vector Machine,Online LS-SVM)的建模方法。Online LS-SVM是以增量学习训练SVM,以减量学习减少样本数,实现小样本估计的训练方法。实验结果表明,Online LS-SVM不仅能实现钢铁件渗碳层深度的在线电磁无损检测,而且具有学习速度快、泛化性能好和对样本依赖程度低的优点。
文摘为了实现钢铁件淬火硬度的在线电磁无损检测,提出了在线最小二乘支持向量机(online least square support vector machine)的建模方法。Online LS-SVM是以增量学习训练SVM,以减量学习减少样本数,实现小样本估计的训练方法。实验结果表明,Online LS-SVM不仅能实现钢铁件淬火硬度的在线电磁无损检测,而且具有学习速度快,泛化性能好,对样本依赖程度低的优点。
文摘In recent years, advanced control technologies have been used for the optimum control of a cold storage. But there are still a lot of shortcomings. One of the main problems is that the traditional methods can't realize the on-line predictive optimum control of a refrigerating system with simple and valid algorithms. An RBF neural network has a strong ability in nonlinear mapping, a good interpolating value performance, and a higher training speed. Thus a two-stage RBF neural network is proposed in this paper. Combining the measured values with the predicted values, the two-stage RBF neural network is used for the on-line predictive optimum control of the cold storage temperature. The application results of the new methods show a great success.
