This article puts forward the experimental methods to analyze the heat exchange process of outside surface of walls of construction by instrumental variable technique and derive the heat exchange coefficient of outside surface of the wall body.
Ordinary Kriging(OK),Co-Kriging(CK) and OKR interpolations were conducted with 72 SOC data in the topsoil(0～10 cm) which was selected as an auxiliary variable,and 36 and 24 SOC data in the subsoil(10～20 cm) as target variables.
On the analying of that there is strong linear relationship between pour point of light diesel oil and secondary variable, the soft-sensing model is established by applying Multivariable Linear Regression (MLR), Partial-Least-Squares Regression (PLSR), BP(Back Propagation)networks and RBF(Radial Basis Function)networks.
Then product between the plant height and stem-diameter of sunflower is marked as the integrated index and regarded as primary variable. Choosing water conter and EC as secondary variable, the integrated index of sunflower is estimated using the three variables CK method that is in the form of covariance function.
On the basis of relative hydromechanical theoretics, weight that is easy to measure is chosen as Secondary Variable and non-linear mathematics model between flux and weight by sample statistics is constructed.
First it gives analysis and comparison to Least Squares, Weighted LeastSquares, Extended Least Squares and Instrumental variables, then analysestheoretically the problems of how to realize the identification in computer.
This paper studies the problem of estimating parameters of ARMA(p,q) with the observed data corrupted by an unknown white noise. A modified recursive instrumental variables(RIV) method is developed to provide consistent estimates for the parameters of AR(p) and variance of the white noise. With these obtained results, estimates of the parameters in MA(q) can be determined by using the welldeveloped Newton-Raphson algorithm.
The instrumental variables are obtained from predictions based on past three bearing measurements and are therefore independent of the present noisy measurements, so a recursive, unbiased estimator is established.
In the proposed method,proper instrumental variables are constructed to suppress the effects of noise on the detection performance,and a useful criterion for detection is derived based on the asymptotical analysis of the orthogonality between signal and noise subspace.
A new method of the instrumental variables is presented based on the research of the current Pseudo-linear estimator(PLE). The simulation result of Cramer-Rao lower bound(CRLB) and root mean square error(RMSE) is obtained after the computer simulation. The algorithm is recursive, unbiased, and stable.
For such plants, the potentials of the two methods of active identification are Compared-the instrumental variable method and the finite-frequency identification method.
Modelling of an hydraulic excavator using simplified refined instrumental variable (SRIV) algorithm
Based on the data collected in the excavator's arms driving experiments, a data-based excavator dynamic model using Simplified Refined Instrumental Variable (SRIV) identification and estimation algorithms is established.
Lattice implementation of the instrumental variable method: Shift and delta operator formulations
The lattice forms of the Instrumental Variable (IV) method is derived, for the standard shift operator.
In this paper, we undertake a small-scale simulation study to examine the magnitude of imprecision introduced in the ratio and regression methods of estimation if the auxiliary variable is contaminated with measurement errors.
The proposed control chart is based on regression type estimator of variance using a single auxiliary variable X.
the main variable under study and the auxiliary variable have a very high negative correlation between them.
Postulating a linear regression of a variable of interest on an auxiliary variable with values of the latter known for all units of a survey population, we consider appropriate ways of choosing a sample and estimating the regression parameters.
The algorithm uses an auxiliary variable for systematic expansion, when necessary, of the linear feasible set to ensure a feasible direction vector.
As health-related quality-of-life (HRQOL) is also supposed to be an important outcome parameter, it was assessed as a secondary variable in these two patient groups.
The Walker Lake data based is used to produce a heterogeneous log-transmissivity field with distinct non-Gaussian characteristics and a secondary variable that represents some geophysical attribute.
For correlations between the principal and secondary variable under 0.4, similar results are obtained using kriging and cokriging, and these methods are superior slightly to the other approaches in terms of minimizing estimation error.
A moderate correlation (approximately r = 0.70) existed between a continuous primary variable and a continuous secondary variable.
Such model is inappropriate in the presence of a smoothly varying secondary variable defined on a much larger volume support than the primary variable.