Research on the identification performance of UHF RFID system considering the correlation of cascaded channel

The identification rate of UHF RFID system was restricted by multipath propagation effects.The system identification performance was studied considering the correlation coefficient between forward and reverse channels.Based on the generalized Rician fading channel model,the analytical expression of identification rate was derived under independent,full correlation and correlation cases.Compared with the existing analysis,the proposed uniform calculation formula of identification rate was for any correlation coefficient and kinds of channel conditions.The numerical computation and Monte-carlo simulations show that the influences of different correlation coefficients,channel conditions,sensitivity and distance on the identification rate.     

Comparison of discriminability of common food acceptance scales for the elderly

This study was aimed to compare four commonly used methods for evaluating consumer acceptance (the 5-point and the 9-point hedonic scales) and preference (the ranking scale and the best-worst scaling) in terms of their ability in discriminating samples and perceived ease of use by the elderly. Elderly (n = 100) and young adult (n = 100) consumers participated in this study. Each consumer evaluated five commercial orange juice samples in duplicate for hedonic rating and preference rank separately and then evaluated ten sets of three samples for the best-worst scale, following the balanced incomplete block design. Nonparametric tests were employed as normality of data was violated. A significant sample effect was observed in all four methods (P < .001). Discriminating power of the best-worst scaling was more pronounced in the elderly than in the young adults; however, the best-worst scaling was easy to use for the young adults than for the elderly.     

蝗虫优化相关向量机模型在径流预测中的应用

针对径流序列不稳定导致预测精度不高的问题,提出一种基于变分模态分解(VMD)和蝗虫优化算法(GOA)优化相关向量机(RVM)的组合径流预测模型。首先对原始非平稳的径流序列采用VMD得到若干个相对稳定的分量序列,再分别建立RVM预测模型,并采用GOA优化RVM中核函数的参数,最后累加所有分量的预测值得到径流序列的预测值。实例结果发现,较传统的BP神经网络、支持向量机及基于经验模态分解的支持向量机等模型,该模型预测精度更高,预测结果能为水电站的经济运行、水资源的有效利用等提供决策依据。     

An evolved VIKOR method for multiple-criteria compromise ranking modeling under T-spherical fuzzy uncertainty

The development of T-spherical fuzzy (T-SF) sets in qualitative multiple-criteria choice analysis has been well investigated, but little is explored about how the VIKOR (i.e., VIšekriterijumsko KOmpromisno Rangiranje in Serbian) mechanism is generalized into intricate T-SF environments. This paper has the objective of propounding a creative T-SF VIKOR methodology for compromise ranking modeling in multiple criteria analysis. The exploitation of the T-SF configuration brings about superior information space representation in response to intricate realistic environments. However, because of the increased complexity of decision situations involving T-spherical fuzziness, treatment with the T-SF information arises a pragmatic difficulty in developing methodological approaches to T-SF VIKOR. In light of this concern, this paper unfolds an analytical framework for the T-SF VIKOR method predicated on new notions of an evolved T-SF score function and the Minkowski-type T-SF distance measure along with its special cases of the Manhattan-, Euclidean-, and Chebyshev-type distances. The aspired and despised T-SF characteristics can be identified supported by the evolved T-SF score function of T-SF performance ratings. This paper gives a new delineation of the group utility, individual regret, and joint generalized measures with the aid of the Minkowski-type T-SF distance measure relative to the aspired/despised T-SF characteristics. A synthetic mechanism is built to validate the standards of acceptable advantage and stability and yield the ultimate compromise choices for multiple criteria decision aiding. The practicality of the T-SF VIKOR methodology in down-to-earth decision situations has been well demonstrated through the selection issues of warehouse locations and advertisement strategies. Moreover, the developed approach has shown better application outcomes than the past methods did. The comparative study with parametric analysis has revealed the steadiness and effectiveness of the compromise choice results in T-SF circumstances.     

The 9‐point hedonic scale and hedonic ranking in food science: some reappraisals and alternatives

The 9‐point hedonic scale has been used routinely in food science, the same way for 60 years. Now, with advances in technology, data from the scale are being used for more and more complex programs for statistical analysis and modeling. Accordingly, it is worth reconsidering the presentation protocols and the analyses associated with the scale, as well as some alternatives. How the brain generates numbers and the types of numbers it generates has relevance for the choice of measurement protocols. There are alternatives to the generally used serial monadic protocol, which can be more suitable. Traditionally, the ‘words’ on the 9‐point hedonic scale are reassigned as ‘numbers’, while other ‘9‐point hedonic scales’ are purely numerical; the two are not interchangeable. Parametric statistical analysis of scaling data is examined critically and alternatives discussed. The potential of a promising alternative to scaling itself, simple ranking with a hedonic R‐Index signal detection analysis, is explored in comparison with the 9‐point hedonic scale. © 2014 Society of Chemical Industry     

基于原位监测的边坡滑动原因初步分析

目前，人们常常借助实验室对边坡滑动的机理进行模拟分析，从而得出各种各样的滑坡模型，这些模型各有千秋、难分伯仲，在适用性方面也各有所长，实践发现，用实验室模型研究成果来代表实际滑坡的代表性误差有时会相当大，甚至有时会出现很大的谬误。从根本上弄清滑坡的实际机理是一个非常重要的问题，以原形监测分析法十余年的原位监测数据为依据，初步分析了边坡滑动的外因与内因，利用数学模拟原理初步总结出了边坡滑动与诸滑坡因素间的关联关系。同时叙述了边坡原位监测的一些行之有效的方法与技术手段（包括GPS、测量机器人等）。     

基于GIS的地下水位动态相关预测模型

辅助专业人员进行地下水位动态预测,为政府进行地下水资源开发利用和监督管理服务。基于GIS技术,从空间数据库提取水位相关数据系列,利用多元线性回归和逐步回归分析方法,建立地下水位与降水量、开采量、蒸发量之间的回归模型进行数据分析和水位预测,采用克里格插值方法生成水位等值线,实现预测结果的可视化表达。预测评价数据来源于空间数据库,预测结果又以空间数据的形式保存到空间数据库中去,便于进一步利用。模型将地下水位动态相关预测方法与GIS结合起来形成应用型GIS专业模型,可用于单井点或区域地下水位动态预测评价。     

Multi-criteria ranking and receptor modelling of airborne fine particles at three sites in the Pearl River Delta region of China

The multi-criteria decision making methods, Preference Ranking Organization METHods for Enrichment Evaluation (PROMETHEE) and Graphical Analysis for Interactive Assistance (GAIA), and the two-way Positive Matrix Factorization (PMF) receptor model were applied to airborne fine particle compositional data collected at three sites in Hong Kong during two monitoring campaigns held from November 2000 to October 2001 and November 2004 to October 2005. PROMETHEE/GAIA indicated that the three sites were worse during the later monitoring campaign, and that the order of the air quality at the sites during each campaign was: rural site > urban site > roadside site. The PMF analysis on the other hand, identified 6 common sources at all of the sites (diesel vehicle, fresh sea salt, secondary sulphate, soil, aged sea salt and oil combustion) which accounted for approximately 68.8 ± 8.7% of the fine particle mass at the sites. In addition, road dust, gasoline vehicle, biomass burning, secondary nitrate, and metal processing were identified at some of the sites. Secondary sulphate was found to be the highest contributor to the fine particle mass at the rural and urban sites with vehicle emission as a high contributor to the roadside site. The PMF results are broadly similar to those obtained in a previous analysis by PCA/APCS. However, the PMF analysis resolved more factors at each site than the PCA/APCS. In addition, the study demonstrated that combined results from multi-criteria decision making analysis and receptor modelling can provide more detailed information that can be used to formulate the scientific basis for mitigating air pollution in the region.     

基于相关向量机的SAR图像飞机目标分类方法研究

随着合成孔径雷达(SAR)成像技术的发展,SAR图像的数据处理和图像分类工作近年来成为研究热点.在本文中,将相关向量机(RVM)应用于SAR图像目标分类识别,对3类飞机仿真目标进行分类,从分类正确率、分类时间、泛化能力和鲁棒性方面全面考察其性能.与支持向量机(SVM)相比,相关向量机没有多余的参数调整,核函数不需要满足Mercer条件,可以获得更多的稀疏模型.仿真结果表明,在对3种类型的飞机仿真目标进行分类的情况下,使用RVM方法总体分类性能略高于SVM.     

一种电网可疑参数诊断方法研究

电网参数错误将影响电力系统状态估计的质量,并降低能量管理系统中其他高级应用软件的实用化程度。当存在多个遥测坏数据和参数错误时,如何保证状态估计结果的有效性非常重要。提出了一种电网可疑参数诊断方法,将参数错误和量测错误在信息空间统一建模,根据加权最小二乘方法计算各量测量的百分比残差并通过阈值比较获得可疑测点集合;计算各可疑测点以及可疑支路的相关度指标,针对各可疑支路逐一采用牛顿下山法求解可疑参数的最优估计,并更新参数集。算例仿真结果表明,该方法能够综合考虑网络参数错误和量测数据错误,并且能够适用于多个错误参数并存的情况,有效地提升了参数辨识与诊断的准确度,对于提高电网运行基础数据的质量与电网高级应用的实用化程度发挥了重要作用。