Study of automatic designing of line heating technique parameters

Based on experimental data of line heating, the methods of vector mapping, plane projection, and coordinate converting are presented to establish the spectra for line heating distortion discipline which shows the relationship between process parameters and distortion parameters of line heating. Back-propagation network （BP-net） is used to modify tile spectra. Mathematical models for optimizing line heating techniques parameters, which include two-objective functions, are constructed. To convert the multi-objective optimization into a single-objective one, the method of changifig weight coefficient is used, and then the individual fitness function is built up, Taking the number of heating lines, distance between the heating lines＇ border （line space）, and shrink quantity of lines as three restrictive conditions, a hierarchy genetic algorithm （HGA） code is established by making use of information provided by the spectra, in which inner coding and outer coding adopt different heredity arithmetic operators in inherent operating, The numerical example shows that the spectra for line heating distortion discipline presented here can provide accurate information required by techniques parameter prediction of line heating process and the technique parameter optimization method based on HGA provided here can obtain good results for hull plate.

Hopping Parameter Expansion Technique in Noise Method for Disconnected Quark Loops

We investigate the effectiveness of the hopping parameter expansion（HPE） combined with the Z（2） noise method in the calculation of the trace of the inverse of Wilson＇s Dirac operator and some other disconnected contributions.A numerical comparison of the standard deviation for the Z（2） noise method and HPE with the Z（2） noise method is carried out. It is found that there are noise reductions in all the quantities we calculated using the HPE with the Z（2） noise method. For the trace of the inverse of Wilson＇s Dirac operator, the HPE can reduce the statistical error by about 60%.

Performance of Weibull function as a diameter distribution model for Pinus thunbergii stands in the eastern coast of South Korea

This study was carried out to determine the performance of percentile-based Weibull diameter distribution model for Pinus thunbergii stands thriving along the eastern coast of South Korea. The parameter recovery technique was used to estimate the three parameters of the Weibull model. The analysis demonstrated satisfactory results based on the following test statistics for the principal percentile models： fit index （FI） range from 0.501（minimum diameter） to 0.932 （50th diameter percentiles） and root mean square error （RMSE） range from 0.112 （quadratic mean diameter） to 3.572 （minimum diameter）. The developed model was further evaluated by determining the mean bias （E） in trees per ha （TPH） for each diameter class, and the results showed highest over-prediction in the 20 cm, and under-prediction in the x6 cm and 24 cm diameter classes. The goodness of fit tested by Kolmogorov- Smirnov （KS） test showed no significant differences （P〉0.05） between the observed and predicted diameter distributions for almost all plots. Using site index and aboveground biomass （AGB） models developed for P. thunbergii in South Korea, a model to predict the AGB per ha for each diameter class and subsequently the total AGB of the stand was created. An application guide was also created, which will serve as a decision-support tool for forest managers in quantifying the future total AGB in P. thunbergii stands located in the eastern coast of South Korea and, subsequently, the quantification of potential carbon stocks aside from being a vital input in designing efficient management and protection strategies for these stands.

High Resolution Multipath Time Delay Estimation Based on FLOCCS-ESPRIT

The non-Gaussian α-stable distribution is introduced to model impulsive noise. Based on the theory of fractional lower order statistics (FLOS), the fractional lower order cross-covariance (FLOCC) sequence for two received signals is obtained and the fractional lower order cross-covariance spectrum (FLOCCS) can be approached by taking a Fourier transform for the FLOCC sequence. When the FLOCCS is treated as a sequence in the time domain, the problem of multipath time delay estimation (TDE) may be converted into one on multi-frequencies estimation or directions of arrival estimation. Accordingly, the high resolution multipath TDE can be realized with the ESPRIT technology. This idea on multipath TDE is referred to as FLOCCS-ESPRIT in this paper. Computer simulations show that this method has good performance both in a Gaussian noise and in an impulsive noise environment.

Covariance Matrix Learning Differential Evolution Algorithm Based on Correlation

Differential evolution algorithm based on the covariance matrix learning can adjust the coordinate system according to the characteristics of the population, which makes the search move in a more favorable direction. In order to obtain more accurate information about the function shape, this paper proposes covariance matrix learning differential evolution algorithm based on correlation (denoted as RCLDE) to improve the search efficiency of the algorithm. First, a hybrid mutation strategy is designed to balance the diversity and convergence of the population;secondly, the covariance learning matrix is constructed by selecting the individual with the less correlation;then, a comprehensive learning mechanism is comprehensively designed by two covariance matrix learning mechanisms based on the principle of probability. Finally, the algorithm is tested on the CEC2005, and the experimental results are compared with other effective differential evolution algorithms. The experimental results show that the algorithm proposed in this paper is an effective algorithm.

COMPENSATION FOR THE MUTUAL COUPLING EFFECT FOR THE ESPRIT ALGORITHM IN SINGLE SNAPSHOT ARRAY PROCESSING

An effective method is introduced to compensate the effects of mutual coupling for the Estimation of Signal Parameter via Rotational Invariance Techniques (ESPRIT) direction finding algorithm in application of signal snapshot array processing.Changing the covariance matrix into a Teoplitz matrix can achieve high resolution in the Direction Of Arrive (DOA) estimation.How the mutual coupling affects the array antennas has been discussed and a new definition of mutual im- pedance has been used to characterize the mutual coupling effects between the array elements.Based on the new mutual impedance matrix,a practical method is presented to eliminate the effects of mutual coupling for ESPRIT in the single snapshot data processing.The simulation results show that, this new method not only properly reduces the effects of mutual coupling,but also maintains its steady performance even for weak signals.

Overall test evaluation based on trajectory tracking data

According to the trajectory characteristics of ballistic missile, a reduced parameter model is constructed based on difference between telemetry trajectory and trajectory tracking data. By virtue of Bayesian theory and data fusion technique, a new test evaluation method is put forth, which can make full use of the trajectory tracking data, shooting range test data and relevant information. Since the impact point can be derived from trajectory difference and its kinetic characteristics, evaluation of the impact point is a special case of this method. The accurate evaluation and the accuracy of evaluation results can be provided by the new method.