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车用锂离子电池剩余使用寿命预测方法 被引量:18
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作者 王常虹 董汉成 +2 位作者 凌明祥 李清华 屈桢深 《汽车工程》 EI CSCD 北大核心 2015年第4期476-479,共4页
剩余使用寿命(RUL)是锂离子电池健康监测与维护的关键参数,反映了电池到寿命终点的剩余工作时间。本文中提出了反映电池健康状态的电池容量衰退参数,利用这些参数建立RUL预测模型。将支持向量回归机粒子滤波应用于参数估计与RUL预测,给... 剩余使用寿命(RUL)是锂离子电池健康监测与维护的关键参数,反映了电池到寿命终点的剩余工作时间。本文中提出了反映电池健康状态的电池容量衰退参数,利用这些参数建立RUL预测模型。将支持向量回归机粒子滤波应用于参数估计与RUL预测,给出了RUL的预测值与概率密度。结果表明提出的方法准确地预测了电池的RUL。 展开更多
关键词 锂离子电池 剩余使用寿命 预测模型 容量衰退参数 支持向量回归机粒子滤波
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Geometric Properties of AR(q) Nonlinear Regression Models
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作者 LIUYing-ar WEIBo-cheng 《Chinese Quarterly Journal of Mathematics》 CSCD 2004年第2期146-154,共9页
This paper is devoted to a study of geometric properties of AR(q) nonlinear regression models. We present geometric frameworks for regression parameter space and autoregression parameter space respectively based on th... This paper is devoted to a study of geometric properties of AR(q) nonlinear regression models. We present geometric frameworks for regression parameter space and autoregression parameter space respectively based on the weighted inner product by fisher information matrix. Several geometric properties related to statistical curvatures are given for the models. The results of this paper extended the work of Bates & Watts(1980,1988)[1.2] and Seber & Wild (1989)[3]. 展开更多
关键词 nonlinear regression model AR(q) errors geometric framework statistical curvature Fisher information matrix
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Path Integral Formalism for Nondegenerate Parametric Amplifiers in Entangled State Representation
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作者 FANHong-Yi LIChao +1 位作者 LIUQiu-Yu AlfredWiinsche 《Communications in Theoretical Physics》 SCIE CAS CSCD 2005年第6期998-1002,共5页
We establish the path integral formalism for nondegenerate parametric amplifiers in the entangled state representations. Its advantage in obtaining the energy level gap of this system is analyzed.
关键词 path integral entangled states nondegenerate parametric amplifier
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A Two-parameter Exponential Recession Model for Simulating Cropland Soil Moisture Dynamics
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作者 SHANG Songhao MAO Xiaomin 《Chinese Geographical Science》 SCIE CSCD 2014年第5期575-586,共12页
To simulate the soil moisture variation in cropland, a two-parameter exponential recession model was derived to depict the recession process of soil moisture in the root zone. The model is based on the assumption that... To simulate the soil moisture variation in cropland, a two-parameter exponential recession model was derived to depict the recession process of soil moisture in the root zone. The model is based on the assumption that the recession rate of soil water is proportional to the potential evapotranspiration rate and the difference of soil water content and steady soil water content. Two parameters in this model are soil texture-dependent recession constant and steady soil water content. The model was calibrated and validated with measured soil water data at two experiment sites in North China with different soil textures and cropping systems. Coefficients of determination between measured and model simulated soil water content were all greater than 0.7, indicating that both models gave satisfactory simulation results. Results showed that values of two parameters mentioned above are both larger for finer soil than those for coarser soil. At the same potential evapotranspiration rate and soil water content, the recession rate of finer soil is usually lower than that of coarser soil. The proposed model can be used in irrigation management to predict approximate date for irrigation, as well as be embedded into watershed hydrological models to estimate the antecedent precipitation index. 展开更多
关键词 soil water content recession process recession coefficient potential evapotranspiration soil texture CROPLAND
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TWO-STAGE ESTIMATION FOR SEEMINGLY UNRELATED NONPARAMETRIC REGRESSION MODELS 被引量:2
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作者 Jinhong YOU Shangyu XIE Yong ZHOU 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2007年第4期509-520,共12页
This paper is concerned with the estimating problem of seemingly unrelated (SU) non- parametric regression models. The authors propose a new method to estimate the unknown functions, which is an extension of the two... This paper is concerned with the estimating problem of seemingly unrelated (SU) non- parametric regression models. The authors propose a new method to estimate the unknown functions, which is an extension of the two-stage procedure in the longitudinal data framework. The authors show the resulted estimators are asymptotically normal and more efficient than those based on only the individual regression equation. Some simulation studies are given in support of the asymptotic results. A real data from an ongoing environmental epidemiologie study are used to illustrate the proposed procedure. 展开更多
关键词 Asymptotic normality nonparametrie model seemingly unrelated regression two-stage estimation
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ASYMPTOTIC NORMALITY OF SOME ESTIMATORS IN A FIXED-DESIGN SEMIPARAMETRIC REGRESSION MODEL WITH LINEAR TIME SERIES ERRORS 被引量:10
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作者 JinhongYOU CHENMin GemaiCHEN 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2004年第4期511-522,共12页
Consider a semiparametric regression model with linear time series errors Y_k= x′ _kβ + g(t_k) + ε_k, 1 ≤ k ≤ n, where Y_k's are responses, x_k =(x_(k1),x_(k2),···,x_(kp))′ and t_k ∈ T is con... Consider a semiparametric regression model with linear time series errors Y_k= x′ _kβ + g(t_k) + ε_k, 1 ≤ k ≤ n, where Y_k's are responses, x_k =(x_(k1),x_(k2),···,x_(kp))′ and t_k ∈ T is contained in R are fixed design points, β =(β_1,β_2,···,β_p)′ is an unknown parameter vector, g(·) is an unknown bounded real-valuedfunction defined on a compact subset T of the real line R, and ε_k is a linear process given byε_k = ∑ from j=0 to ∞ of ψ_je_(k-j), ψ_0=1, where ∑ from j=0 to ∞ of |ψ_j| < ∞, and e_j,j=0, +-1, +-2,···, ard i.i.d. random variables. In this paper we establish the asymptoticnormality of the least squares estimator of β, a smooth estimator of g(·), and estimators of theautocovariance and autocorrelation functions of the linear process ε_k. 展开更多
关键词 semiparametric regression model fixed-design asymptotic normality lineartime series errors
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AN ALGORITHM FOR MAXIMUM LIKELIHOOD ESTIMATES TO SEMI-PARAMETRIC REGRESSION MODEL WITH INTERVAL CENSORED DATA
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作者 ZHANGAijun CHENJiading LIULiping WANGQingcheng 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2004年第3期437-444,共8页
In this paper we study the practical procedure for getting the maximumlikelihood estimates in a semi-parametric regression model with interval censored data.On the basis of the on previous theoretical results, we give... In this paper we study the practical procedure for getting the maximumlikelihood estimates in a semi-parametric regression model with interval censored data.On the basis of the on previous theoretical results, we give the detailed algorithms when there are one or two covariates in the model. 展开更多
关键词 interval censoring profile maximum likelihood method regression analysis RELIABILITY
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