为国际信息计量学发展提供中国学者的解决方案——评邱均平教授团队《信息计量学》英文版

《informetrics:theory,methods and applications(信息计量学:理论,方法和应用)》记录了不同时期信息计量学的研究内容,揭示了“三计学”向“五计学”的发展动因,对信息计量学的未来趋势研究具有重要意义。本文通过回顾邱均平教授团队“三计学”、“五计学”的研究发展史,结合书籍的章节内容、创新点、实用性等方面,对其在国际信息计量学领域的学术影响力以及贡献程度进行分析和总结。可以看出,《informetrics:theory,methods and applications(信息计量学:理论,方法和应用)》不仅仅阐释了信息计量学完整的研究范式,还向全世界展现了中国信息计量研究的多维度突破与创新,为国际信息计量学发展提供新思路。

内蒙古达赉湖地区蒙原羚的春季生境选择

2006年5-6月和2007年5-6月,我们在内蒙古达赉湖地区开展了蒙原羚春季生境选择研究。我们设置样线20条,共记录到蒙原羚64群次、453只次和蒙原羚活动痕迹243处。我们选择了20个与蒙原羚生境选择相关的生境因子,运用信息理论方法和Logistic回归方程,建立了蒙原羚出现与否与各生境因子之间的预测模型。运用资源选择函数和资源选择指数,揭示蒙原羚对各生境因子的选择性。结果表明：家畜干扰是影响蒙原羚春季生境选择的首要因子（β=10.898）;坡位、水源距离、坡度、隐蔽条件、围栏距离和植被类型对蒙原羚春季生境选择有重要作用（β〉1.000）;道路距离、地上生物量、植被高度、植物种类数、植被盖度等因子对蒙原羚春季生境选择影响不显著（β〈1.000）。蒙原羚对牲畜距离〈2000m和〉4000m,中下坡位及平地,水源距离4000-8000m,坡度〈10°,隐蔽条件（可视距离）〈3000m,离围栏距离1000-2000m的针茅和杂草植被类型生境有一定偏好。因此,春季蒙原羚保护的关键是降低放牧强度,应在边境地区控制牲畜数量和人口迁入,在离边境线较远地区进行草场科学管理和制定合理的放牧制度。在植被生长状况较差和水源缺乏年份,应适当进行食物和水源人工补给。另外,进行草场封育,加强打草监管并建立合理的围栏管理制度,也是蒙原羚保护的重要环节。

Natural environment suitability for human settlements in China based on GIS

With the degeneration of environment and acceleration of urbanization,human environment has attracted great attention worldwide.This paper sets up the Human Settlements Environment Index(HEI) model and evaluates the natural environment suitability for Human Settlements in China based on GIS technology.The results show that the HEI of China decreases from southeast to northwest in general,HEI is significantly correlated with population density at grid size and the correlation coefficient(r) between them reaches 0.93,which indicates that natural environment suitability for Human Settlements has a significant influence on population distribution.Most people in China mainly concentrate in areas with high natural environment suitability.The total suitable area is 430.47×104 km2,which accounts for nearly 45% of the total land area in China,while the proportion of people living in the area reaches 96.56%.With a population density of 18 people per square kilometer,the critical area is the transitional region for people to live in China.The critical area covers 225.11×104 km2 with a population of 41.12 million.The non-suitable area covers 304.42×104 km2 with a population of only 2.49 million.

Maneuvering Target Tracking Algorithm Based on Muti-paramter Sequential Extended Kalman Filter

Based on the information theory,the performance of maneuvering target tracking can be improved by increasing the input information( observation vector).In this paper,the estimations of radial acceleration and radial velocity obtained in the signal processing are introduced into the measurement vector by coordinate transformation.In order to solve the problem of high nonlinearity of the radial acceleration,radial velocity and the state vector,a new algorithm of multi-parameter sequential extended Kalman filter( MSEKF) is proposed.The tracking performance of this algorithm is tested and compared with the other tracking algorithms.It is shown that the proposed algorithm outperforms these algorithms in strong and weak maneuvering environments.

Optimization model of unascertained measurement for underground mining method selection and its application

An optimization model of underground mining method selection was established on the basis of the unascertained measurement theory.Considering the geologic conditions,technology,economy and safety production,ten main factors influencing the selection of mining method were taken into account,and the comprehensive evaluation index system of mining method selection was constructed.The unascertained evaluation indices corresponding to the selected factors for the actual situation were solved both qualitatively and quantitatively.New measurement standards were constructed.Then,the unascertained measurement function of each evaluation index was established.The index weights of the factors were calculated by entropy theory,and credible degree recognition criteria were established according to the unascertained measurement theory.The results of mining method evaluation were obtained using the credible degree criteria,thus the best underground mining method was determined.Furthermore,this model was employed for the comprehensive evaluation and selection of the chosen standard mining methods in Xinli Gold Mine in Sanshandao of China.The results show that the relative superiority degrees of mining methods can be calculated using the unascertained measurement optimization model,so the optimal method can be easily determined.Meanwhile,the proposed method can take into account large amount of uncertain information in mining method selection,which can provide an effective way for selecting the optimal underground mining method.

Security analysis of access control model in hybrid cloud based on security entropy

To resolve the problem of quantitative analysis in hybrid cloud,a quantitative analysis method,which is based on the security entropy,is proposed.Firstly,according to the information theory,the security entropy is put forward to calculate the uncertainty of the system' s determinations on the irregular access behaviors.Secondly,based on the security entropy,security theorems of hybrid cloud are defined.Finally,typical access control models are analyzed by the method,the method's practicability is validated,and security and applicability of these models are compared.Simulation results prove that the proposed method is suitable for the security quantitative analysis of the access control model and evaluation to access control capability in hybrid cloud.

Multi-factors decision-making entropy method and its application in engineering management

In order to meet the strict requirements for information in engineering management, the positive interval （0, 1 ] in Shannon information entropy is extended to the real number interval [ - 1, 1 ]. The information theory and the decision theory are combined effectively, and the deficiencies that the traditional Bayes decision-making methods only consider a single factor are made up for. The multi-factors engineering decision-making methods are proposed, and some critical problems are solved in the practical engineering management decision-making process.

Attribute reduction in interval-valued information systems based on information entropies

Interval-valued data appear as a way to represent the uncertainty affecting the observed values. Dealing with interval-valued information systems is helpful to generalize the applications of rough set theory. Attribute reduction is a key issue in analysis of interval-valued data. Existing attribute reduction methods for single-valued data are unsuitable for interval-valued data. So far, there have been few studies on attribute reduction methods for interval-valued data. In this paper, we propose a framework for attribute reduction in interval-valued data from the viewpoint of information theory. Some information theory concepts, including entropy, conditional entropy, and joint entropy, are given in interval-valued information systems. Based on these concepts, we provide an information theory view for attribute reduction in interval-valued information systems. Consequently, attribute reduction algorithms are proposed. Experiments show that the proposed framework is effective for attribute reduction in interval-valued information systems.