| 1. | Fuzzy svms for regression estimation are developed in chapter 2
针对回归估计问题提出了模糊svm 。 |
| 2. | A regressive prediction model containing recursive kernel regression estimation
一种包含递归的核回归估计的回归预测模型 |
| 3. | ( 3 ) the performance of support vector machine ( svm ) for regression estimation was studied
( 3 )支持向量机( svm )的参数对其回归估计性能有很大影响。 |
| 4. | In this class we describe support vector machines for regression estimation and illustrate the connection between svms and basis pursuit de - noising
课中将叙述支持向量机的回归估算法并举例说明支持向量机和基础追踪去杂讯法之间的关系。 |
| 5. | For the regression estimation when the auxiliary variate is correlated with the disturbance , the bias and mean square error ( mse ) of the regression estimator are obtained , and the estimator of the mse is presented
摘要讨论了辅助变量与扰动项相关条件下的回归估计，给出了在这种条件下回归估计量的偏差和均方误差以及均方误差的估计。 |
| 6. | By applying generalized svm and least square svm of classification to regression estimation problem , fuzzy generalized weighted svm and fuzzy multiplayer least square generalized svm are proposed . 3
把针对分类问题的广义svm及最小二乘广义svm用来处理回归估计问题，并和模糊svm结合起来形成了基于模糊加权的广义svm和基于模糊的多层最小二乘广义svm 。 |
| 7. | Svm , developed from that theoretical architecture , is a highly adaptive method , which is applied in the areas of pattern recognition , regression estimation , function approximation and density estimation
在这一理论基础上发展了一种新的通用学习方法一支撑向量机svm 。它是一种普遍适用的方法，已经广泛的用于模式识别、回归估计、函数逼近、密度估计等方面。 |
| 8. | Fuzzy c - clustering svm and least square svm for multiclass regression estimations is presented in chapter 3 , this method can estimate multiple regressions while clustering the samples . multi - output svm and multi - output least square svm are discussed for multiclass regression estimations
在讨论多类回归模型估浙江大学博士学位论文计问题的基础上又针对多个输出的问题讨论了svm和ls一svm如何实现的问题。 |
| 9. | In this paper , an integral scheme of 16 position error calibration and autonomous alignment for three axis platform is given . it may calibrate 33 errors in all . first , determine parameters with least square estimate , then bayes method , ridge regression estimation were discussed separately
本文设计了一个十六位置误差标定方案,可以分离出总计33项误差,首先用最小二乘估计方法进行参数辨识,而后,分别研究了基于bayes方法的误差系数辨识,基于岭估计的误差系数辨识。 |
| 10. | Since the range estimation is very important in the power system , after monte - carlo simulation method for the ranks is presented in this paper , and using binomial regression estimation to finish the three parameters range estimation . finally , the flowchart and the example of application of the three parameters range estimation is accomplished
由于区间估计在工程应用中更具有实际意义，本文提出了采用monte - carlo模拟法估计出分位秩后，再进行二项式回归处理来实现三参数区间估计的新方法，并用此方法实现了三参数的区间估计，同时给出了三参数区间估计的程序框图和应用实例。 |
