灰色系统趋势关联度探讨

本文提出灰色系统趋势关联度的概念及计算式。数量关联度从整体数量上、而趋势关联度则从变化趋势上,分别对灰因素进行关联度计算,进而对灰色系统作全面关联分析。趋势关联度还能进一步从中分离提取有用信息,以探求变化原因。文中附以实例说明趋势关联度的实用意义。

Quantum Secure Direct Intercommunication with Superdense Coding and Entanglement Swapping

A quantum secure direct intercommunication scheme is proposed to exchange directly the communicators＇ secret messages by making ase of swapping entanglement of Bell states. It has great capacity to distribute the secret messages since these messages have been imposed on high-dimensional Bell states via the local unitary operations with superdense coding. The security is ensured by the secure transmission of the travel sequences and the application of entanglement swapping.

Evaluating the Algorithm for Correction of the Bright Band Effects in QPEs with S-, C-and X-Band Dual-Polarized Radars

The bright band, a layer of enhanced radar reflectivity associated with melting ice particles, is a major source of signifi- cant overestimation in quantitative precipitation estimation （QPE） based on the Z-R （reflectivity factor-rain rate） relationship. The effects of the bright band on radar-based QPE can be eliminated by vertical profile of reflectivity （VPR） correction. In this study, we applied bright-band correction algorithms to evaluate three different bands （S-, C- and X-band） of dual-polarized radars and to reduce overestimation errors in Z-R relationship-based QPEs. After the reflectivity was corrected by the algo- rithms using average VPR （AVPR） alone and a combination of average VPR and the vertical profile of the copolar correlation coefficient （AVPR＋CC）, the QPEs were derived. The bright-band correction and resulting QPEs were evaluated in eight precipitation events by comparing to the uncorrected reflectivity and rain-gange observations, separately. The overestimation of Z-R relationship-based QPEs associated with the bright band was reduced after correction by the two schemes for which hourly rainfall was less than 5 mm. For the verification metrics of RMSE （root-mean-square error）, RMAE （relative mean absolute error） and RMB （relative mean bias） of QPEs, averaged over all eight cases, the AVPR method improved from 2.28, 0.94 and 0.78 to 1.55, 0.60 and 0.40, respectively, while the AVPR＋CC method improved to 1.44, 0.55 and 0.30, respectively. The QPEs after AVPR＋CC correction had less overestimation than those after AVPR correction, and similar conclusions were drawn for all three different bands of dual-polarized radars.

Damage Identification in Beam-Type Structures Using Pseudo Strain Energy Density and Grey Relation Coefficient

Based on pseudo strain energy density (PSED) and grey relation coefficient (GRC), an index is proposed to locate the damage of beam-type structures in time-domain. The genetic algorithm (GA) is utilized to identify the structural damage severity of confirmed damaged locations. Furthermore, a systematic damage identification program based on GA is developed on MATLAB platform. ANSYS is employed to conduct the finite element analysis of complicated civil engineering structures, which is embedded with interface technique. The two-step damage identification is verified by a finite element model of Xinxingtang Highway Bridge and a laboratory beam model based on polyvinylidens fluoride (PVDF). The bridge model was constructed with 57 girder segments, and simulated with 58 measurement points. The damaged segments were located accurately by GRC index regardless of damage extents and noise levels. With stiffness reduction factors of detected segments as variables, the GA program evolved for 150 generations in 6 h and identified the damage extent with the maximum errors of 1% and 3% corresponding to the noise to signal ratios of 0 and 5%, respectively. In contrast, the common GA-based method without using GRC index evolved for 600 generations in 24 h, but failed to obtain satisfactory results. In the laboratory test, PVDF patches were used as dynamic strain sensors, and the damage locations were identified due to the fact that GRC indexes of points near damaged elements were smaller than 0.6 while those of others were larger than 0.6. The GA-based damage quantification was also consistent with the value of crack depth in the beam model.

An intuitive general rank-based correlation coefficient

Correlation analysis is an effective mechanism for studying patterns in data and making predictions.Many interesting discoveries have been made by formulating correlations in seemingly unrelated data. We propose an algorithm to quantify the theory of correlations and to give an intuitive, more accurate correlation coefficient.We propose a predictive metric to calculate correlations between paired values, known as the general rank-based correlation coefficient. It fulfills the five basic criteria of a predictive metric： independence from sample size,value between-1 and 1, measuring the degree of monotonicity, insensitivity to outliers, and intuitive demonstration.Furthermore, the metric has been validated by performing experiments using a real-time dataset and random number simulations. Mathematical derivations of the proposed equations have also been provided. We have compared it to Spearman＇s rank correlation coefficient. The comparison results show that the proposed metric fares better than the existing metric on all the predictive metric criteria.

Effect of Transverse Correlation Function on the Thermodynamic Quantities of Ferromagnetic Systems

The effect of transverse correlation between spins on the thermodynamic properties of ferromagnetic systems is investigated in details. Qualitatively, at finite temperature the transverse correlation reflects the short-range interaction between spins, so that lowers the internal energy and consequently raises the free energy. It also means the introduction o[ some ordering, and hence lowers the entropy. It is depressed by the field which forces the spins to turn to the field direction, so that it decreases with the field when temperature is fixed. The low-temperature expansion of the energy shows that the inclusion of the transverse correlation at least partly considers the interaction between spin waves.