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1.
Joint application of feature extraction based on EMD-AR strategy and multi-class classifier based on LS-SVM in EMG motion classification 总被引：2，自引：0，他引：2
YAN Zhi-guo WANG Zhi-zhong REN Xiao-mei 《浙江大学学报(A卷英文版)》2007,8(8):1246-1255
This paper presents an effective and efficient combination of feature extraction and multi-class classifier for motion classification by analyzing the surface electromyografic(sEMG) signals. In contrast to the existing methods,considering the non-stationary and nonlinear characteristics of EMG signals,to get the more separable feature set,we introduce the empirical mode decomposition(EMD) to decompose the original EMG signals into several intrinsic mode functions(IMFs) and then compute the coefficients of autoregressive models of each IMF to form the feature set. Based on the least squares support vector machines(LS-SVMs) ,the multi-class classifier is designed and constructed to classify various motions. The results of contrastive experiments showed that the accuracy of motion recognition is improved with the described classification scheme. Furthermore,compared with other classifiers using different features,the excellent performance indicated the potential of the SVM techniques embedding the EMD-AR kernel in motion classification. 相似文献
2.
Short-term load forecasting (STLF) plays a very important role in improving the economy and security of electricity system operations. In this paper, a hybrid STLF method is proposed based on the improved ensemble empirical mode decomposition (IEEMD) and back propagation neural network (BPNN). To alleviate the mode mixing and end-effect problems in traditional empirical mode decomposition (EMD), an IEEMD is presented based on the degree of wave similarity. By applying the IEEMD method, the nonlinear and nonstationary original load series is decomposed into a finite number of stationary intrinsic mode functions (IMFs) and a residual. Among these components, the high frequency (namely IMF1) is always so small that it has little contribution to model fitting, while it sometimes has a great disturbance for the STLF. Therefore, the IMF1 is removed in the proposed hybrid method for denoising. The remaining IMFs and residual are forecast by BPNN, and then the forecasting results of each component are combined with BPNN to obtain the final predicted load series. Three groups of studies were done to evaluate the effectiveness of the proposed hybrid method. The results show that the proposed hybrid method outperforms other methods both mentioned in this paper and previous studies in terms of all the three standard statistical indicators considered in this study. 相似文献
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A new algorithm, named segmented second empirical mode decomposition （EMD） algorithm, is proposed in this paper in order to reduce the computing time of EMD and make EMD algorithm available to online time-frequency analysis. The original data is divided into some segments with the same length. Each segment data is processed based on the principle of the first-level EMD decomposition. The algorithm is compared with the traditional EMD and results show that it is more useful and effective for analyzing nonlinear and non-stationary signals. 相似文献
5.
利用MATLAB编程软件,分别建立BP神经网络和AR模型,采用全国出生率,死亡率,老年抚养率等9个指标作为样本,分别对BP网络和AR模型进行训练,预测5年后的人口数量.结果表明这两种方法预测人口均是可行的,效果较好,误差很小,但是AR模型较适合线性预测,而BP网络适合较非线性预测. 相似文献
6.
It has been shown in recent economic and statistical studies that combining forecasts may produce more accurate forecasts than individual ones,However,the literature on combining forecasts has almost exclusively focused on linear combining forecasts.In this paper,a new nonlinear combination forecasting method based on fuzzy inference system is present to overcome the difficulties and drawbacks in linear combination modeling of non-stationary time series.Furthermore,the optimization algorithm based on a hierarchical structure of learning automata is used to identify the parameters of the fuzzy system.Experiment results related to numerical examples demonstrate that the new technique has excellent identification performances and forecasting accuracy superior to other existing linear combining forecasts. 相似文献
7.
结合经验模态分解（empiricalmodedecomposition,EMD）算法和自适应神经模糊推理系统（adap-tiveneuralfuzzyinferencesystem,ANFIS）算法应用于股票市场预测,提出了一种新的股票市场的预测模型,即EMD-ANFIS的多步预测模型。首先应用EMD算法把原始数据分解成不同尺度的基本模态函数（IMF）和残差（RES）,然后通过ANFIS算法对生成的各个IMF和RES进行自适应神经模糊推理,再把各个预测结果进行简单的聚合作为股票的预测价格,并与传统的预测方法进行比较,实验证明了EMD-ANFIS的多步预测模型具有更高的预测精度。 相似文献
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时间序列分析在水文预报中起重要作用 ,其关键是要建立一个合适的预报模型 .文章提出基于 BP算法的单输出和多输出水文预报时间序列神经网络模型 ,克服了以往多种基于随机分析预报模型的缺点 ,不仅能实现快速灵活的信息处理 ,而且具有很强的非线性映射和自学习、自适应能力 ,这为更精确描述复杂非线性水文过程提供了可能 .通过对历史数据的学习 ,模型可对水文径流量时间序列进行预报 ,两个实例分析表明模型的可行性和有效性 相似文献
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介绍了时间序列的子集门限自回归模型,该模型可以复现非线性时间序列的周期性或季节性趋势．文中给出了子集门限自回归模型的辨识方法并应用于电力负荷的建模和短期预报．应用实例表明,其预测精度较高． 相似文献
10.
二维HM方程解的衰减 总被引：1，自引：0，他引：1
陈静 《楚雄师范学院学报》2012,27(3):44-50
Hasegawa-Mima(简记为HM)方程是研究漂移波和湍流漂移波的模型。本文运用"Fourier-Splitting"技术得到了二维HM方程初始问题解的L2衰减估计和L∞衰减估计。 相似文献
11.
市场价格预测模型体系研究 总被引：3，自引：0，他引：3
目前对市场价格的预测主要是依靠单一的模型,预测结果的准确性直接受到模型的局限。章通过对一套市场价格预测模型体系的介绍,综合运用时问序列模型、多元非线性回归和组合模型来预测市场价格走势,探索从多角度综合预测市场价格的问题。并将该模型体系在某钢铁企业中进行实际运用验证。 相似文献
12.
The explosion inside tunnel would generate blast wave which transmits through the longitudinal tunnel. Because of the close-in effects of the tunnel and the reflection by the confining tunnel structure, blast wave propagation inside tunnel is distinguished from that in air. When the explosion happens inside tunnel, the overpressure peak is higher than that of explosion happening in air. The continuance time of the blast wave also becomes longer. With the help of the numerical simulation finite element software LS-DYNA, a three-dimensional nonlinear dynamic simulation analysis for an explosion experiment inside tunnel was carried out. LS-DYNA is a fully integrated analysis program specifically designed for nonlinear dynamics and large strain problems. Compared with the experimental results, the simulation results have made the material parameters of numerical simulation model available. By using the model and the same material parameters, many results were adopted by calculating the model under different TNT explosion dynamites. Then the method of dimensional analysis was used for the simulation results. As overpressures of the explosion blast wave are the governing factor in the tunnel responses, a formula for the explosion blast wave over-pressure at a certain distance from the detonation center point inside the tunnel was derived by using the dimensional analysis theory. By comparing the results computed by the formula with experimental results which were obtained before, the formula was proved to be very applicable at some instance. The research may be helpful to estimate rapidly the effect of internal explosion of tunnel on the structure. 相似文献
13.
畸形波是一种波高极大的极端非线性波浪,容易对海洋结构物产生巨大破坏.基于畸形波生成机制和水槽自定义造波方法,探讨了畸形波在实验室波浪水槽中的重构方法,主要涉及造波机电压信号的调制解调和迭代优化.在水槽中实现了色散聚焦畸形波典型工况.结果表明,该重构方法能够准确快速地模拟所需的畸形波波面,可为畸形波实验研究提供参考. 相似文献
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孤波在深度缓变矩形槽中满足的方程是含有缓变系数的非线性薛定谔方程,讨论了两种特定情况下方程的孤波解,数值模拟了单个非传播性孤波和两非传播性孤波的演化情况。 相似文献
15.
Longitudinal data are often collected in waves in which a participant’s data can be collected at different times within each wave, resulting in sampling-time variation that is unaccounted for when waves are treated as single time points. Little research has been reported on the effects of this temporal imprecision on longitudinal growth-curve modeling. This article describes the results of a simulation study into the effect of sampling-time variation on parameter estimation, model fit, and model comparison with an empirical validation of the model fit and comparison results. 相似文献
16.
弱非线性水波在非平整海底上传播可以产生各种类型的波群解．在缓变和局部快变的水深情形下,描述了三阶演化方程的色散项和非线性项的零点的变化性质,并得到了该方程的波群解． 相似文献
17.
Car following model is one of microscopic models for describing traffic flow. Through linear stability analysis, the neutral stability lines and the critical points are obtained for the different types of car following models and two modified models. The singular perturbation method has been used to derive various nonlinear wave equations, such as the Korteweg-de-Vries (KdV) equation and the modified Korteweg-de-Vries (mKdV) equation, which could describe different density waves occurring in traffic flows under certain conditions. These density waves are mainly employed to depict the formation of traffic jams in the congested traffic flow. The general soliton solutions are given for the different types of car following models, and the results have been used to the modified models efficiently. 相似文献
18.
The surface acoustic wave (SAW) propagating in a sample of steel is simulated by using finite element method (FEM). The waves are excited by a load function with propagation properties such as phase velocity dispersion and wide bandwidth. A two-dimensional model consisting of surface defects loaded with a wideband 50-200 MHz and short time 0.1 μs displacement function is investigated in the time and frequency domains. By transient dynamic analysis, Fourier transform and dispersion calculation, snapshots of propagating wave and responses from sensing points are presented. It is indicated that this supervision approach is sensitive to the surface cracks and reflections. 相似文献
19.
TABESHPOUR M.R. GOLAFSHANI A.A. SEIF M.S. 《浙江大学学报(A卷英文版)》2006,7(8):1305-1317
INTRODUCTION There is obvious demand for oil exploitation in deep water. Increasing water depth will make the environment more severe and so some innovative structures are required for economic production of gas and petroleum in deep water. An engineering idea is the minimization of the structure resistance to en-vironmental loads by making the structure flexible. This structural flexibility causes nonlinearity in the structural stiffness matrix because of large deforma-tions. Wave loadi… 相似文献
20.
符保龙 《柳州职业技术学院学报》2009,9(1):81-85
针对BP神经网络的不足,采用PSO算法对BP神经网络进行优化,建立一个混合的神经网络洪水预测模型。实验仿真结果表明,该模型的预测效果优于传统的洪水预测模型。 相似文献