An Adaptive Lasso Grey Model for Regional FDI Statistics Prediction

To overcome the deficiency of traditional mathematical statistics methods,an adaptive Lasso grey model algorithm for regional FDI(foreign direct investment)prediction is proposed in this paper,and its validity is analyzed.Firstly,the characteristics of the FDI data in six provinces of Central China are generalized,and the mixture model’s constituent variables of the Lasso grey problem as well as the grey model are defined.Next,based on the influencing factors of regional FDI statistics(mean values of regional FDI and median values of regional FDI),an adaptive Lasso grey model algorithm for regional FDI was established.Then,an application test in Central China is taken as a case study to illustrate the feasibility of the adaptive Lasso grey model algorithm in regional FDI prediction.We also select RMSE(root mean square error)and MAE(mean absolute error)to demonstrate the convergence and the validity of the algorithm.Finally,we train this proposedal gorithm according to the regional FDI statistical data in six provinces in Central China from 2006 to 2018.We then use it to predict the regional FDI statistical data from 2019 to 2023 and show its changing tendency.The extended work for the adaptive Lasso grey model algorithm and its procedure to other regional economic fields is also discussed.

Application of Integration of Spatial Statistical Analysis with GIS to Regional Economic Analysis

This paper summarizes a few spatial statistical analysis methods for to measuring spatial autocorrelation and spatial association, discusses the criteria for the identification of spatial association by the use of global Moran Coefficient, Local Moran and Local Geary. Furthermore, a user-friendly statistical module, combining spatial statistical analysis methods with GIS visual techniques, is developed in Arcview using Avenue. An example is also given to show the usefulness of this module in identifying and quantifying the underlying spatial association patterns between economic units.

Comparison of Statistical Models for Regional Crop Trial Analysis

Based on the review and comparison of main statistical analysis models for estimating variety-environment cell means in regional crop trials, a new statistical model, LR-PCA composite model was proposed, and the predictive precision of these models were compared by cross validation of an example data. Results showed that the order of model precision was LR-PCA model > AMMI model > PCA model > Treatment Means (TM) model > Linear Regression (LR) model > Additive Main Effects ANOVA model. The precision gain factor of LR-PCA model was 1.55, increasing by 8.4% compared with AMMI.

The Statistical Significance Test of Regional Climate Change Caused by Land Use and Land Cover Variation in West China

The West Development Policy being implemented in China is causing significant land use and land cover （LULC） changes in West China. With the up-to-date satellite database of the Global Land Cover Characteristics Database （GLCCD） that characterizes the lower boundary conditions, the regional climate model RIEMS-TEA is used to simulate possible impacts of the significant LULC variation. The model was run for five continuous three-month periods from 1 June to 1 September of 1993, 1994, 1995, 1996, and 1997, and the results of the five groups are examined by means of a student t-test to identify the statistical significance of regional climate variation. The main results are： （1） The regional climate is affected by the LULC variation because the equilibrium of water and heat transfer in the air-vegetation interface is changed. （2） The integrated impact of the LULC variation on regional climate is not only limited to West China where the LULC varies, but also to some areas in the model domain where the LULC does not vary at all. （3） The East Asian monsoon system and its vertical structure are adjusted by the large scale LULC variation in western China, where the consequences are the enhancement of the westward water vapor transfer from the east oast and the relevant increase of wet-hydrostatic energy in the middle-upper atmospheric layers. （4） The ecological engineering in West China affects significantly the regional climate in Northwest China, North China and the middle-lower reaches of the Yangtze River; there are obvious effects in South, Northeast, and Southwest China, but minor effects in Tibet.

The Statistical Analysis of Migration of Strong Earthquakes─Taking the North China Region as an Example

The migration of strong earthquakes is an important research topic because the migration phenomena reflect partly the seismic mechanism and involve the prediction of tendency of seismic activity. Research on migration of strong earthquakes has mostly focused on finding the phenomena. Some attempts on getting regularity were comparatively subjective. This paper suggests that there should be indices of migration in earthquake dataset and the indexes should have statistical meaning if there is regularity in the migration of strong earthquakes. In this study, three derivative attributes of migration, i.e., migration orientation, migration distance and migration time interval, were statistically analyzed. Results in the North China region show that the migration of strong earthquakes has statistical meaning. There is a dominant migration orientation (W by S to E by N), a dominant distance (≤100km and on the confines of 300～700km), and a dominant time interval (≤1a and on the confines of 3～4a). The results also show that the migration will differ slightly with different magnitude range or earthquake activity phase.

Interrelation between seismicity parameters and delimiting potential seismic sources in a seismic statistical region and its influence on seismic risk estimation

In the paper, we have discovered the abnormal area distribution features of maximum variation values of ground motion parameter uncertainty with different probabilities of exceedance in 50 years within the range of 100°-120°E, 29°-42°N for the purpose to solve the problem that abnormal areas of maximum variation values of ground motion parameter uncertainties emerge in a certain cities and towns caused by seismicity parameter uncertainty in a seismic statistical region in an inhomogeneous distribution model that considers tempo-spatial nonuniformity of seismic activity. And we have also approached the interrelation between the risk estimation uncertainty of a site caused by seismicity parameter uncertainty in a seismic statistical region and the delimitation of potential sources, as well as the reasons for forming abnormal areas. The results from the research indicate that the seismicity parameter uncertainty has unequal influence on the uncertainty of risk estimation at each site in a statistical region in the inhomogeneous distribution model, which relates to the scheme for delimiting potential sources. Abnormal areas of maximum variation values of ground motion parameter uncertainty often emerge in the potential sources of Mu greater than or equal 8 (Mu is upper limit of a potential source) and their vicinity. However, this kind of influence is equal in the homogeneous distribution model. The uncertainty of risk estimation of each site depends on its seat. Generally speaking, the sites located in the middle part of a statistical region are only related to the seismicity parameter uncertainty of the region, while the sites situated in or near the juncture of two or three statistical regions might be subject to the synthetic influences of seismicity parameter uncertainties of several statistical regions.

STATISTICS OF CHINA'S TEXTILE JOURNALS

This paper deals with the number of China’s textile journals,and the distribution of journalsincluding the content,region and publishing organization.Based on investigation,the number ofjournals now probably exceeds 300,their contents cover all the textile fields,and the publishing or-ganizations with various form are all over the country.

CONFIDENCE REGIONS IN TERMS OF STATISTICAL CURVATURE FOR AR(q) NONLINEAR REGRESSION MODELS

This paper constructs a set of confidence regions of parameters in terms of statistical curvatures for AR(q) nonlinear regression models. The geometric frameworks are proposed for the model. Then several confidence regions for parameters and parameter subsets in terms of statistical curvatures are given based on the likelihood ratio statistics and score statistics. Several previous results, such as [1] and [2] are extended to AR(q) nonlinear regression models.

Tidal triggering of seismicity in the region of Palu, Central Sulawesi, Indonesia

This paper investigates the correlation between tidal stress and earthquakes for periods ranging from hours to months in the limited zone of the Palu region(Central Sulawesi,Indonesia).Through Schuster and binomial tests,we examined the relation between the seismicity(time density of seismic events)and tidal potential arising from the Moon and Sun,using all tidal components simultaneously and focusing on the estimation of specific terms.The results show significant correlations between the seismicity and tidal potential for S2(0.5 d)and O1(1.075 d)tidal components in the case of solely isolated earthquake events,particularly for shallow earthquakes.Meanwhile,there is a strong relationship between aftershocks and tidal components larger than the Mf period(13.661 d).Finally,the analysis of the temporal variation of the earthquake-tide relation reveals an optimal correlation for about six years before the 2018 great Palu earthquake.The correlation becomes insignificant afterwards.

机器学习在人工增雨效果统计检验中的应用

利用福建省古田人工增雨试验基地2014年1月—2023年1月小时自然降水数据,结合线性拟合、多项式回归和样条回归等多种数学统计方法,开展决策树、支持向量机(SVM)和卷积神经网络(CNN)3种机器学习方法在估测目标区自然降水中的应用研究。目标区和对比区自然雨量关系模型对比结果表明:以区域平均面雨量为统计变量时,CNN和四项式回归效果相对较好,其中CNN的确定系数为0.516,均方根误差为1.097 mm;对平均面雨量进行六次方根变换后,各模型的精准度大幅提升,CNN表现最优,确定系数为0.658,其次为SVM;为克服目标区和对比区雨量时间序列效应及空间分布不均等问题,以面雨量空间格点数据作为研究对象,采用CNN 3种优化器(自适应矩估计、均方根传递和梯度随机下降)算法进行对比,发现基于自适应矩估计优化器建立目标区和对比区雨量关系模型最优,其降水估测值与实测值更接近,均方根误差最小,为0.61 mm。因此,利用CNN方法能够进一步优化目标区和对比区雨量关系模型,可为定量评估人工增雨效果提供参考。

寒区隧道内气温分布特征及影响因素

受严寒气候影响,寒冷地区的隧道工程普遍面临不同程度的衬砌挂冰、冻融损伤甚至开裂、路面结冰、排水系统冻结失效等一系列冻害问题,给隧道工程的建设和运营带来了极大的挑战。负温环境是隧道冻害产生的必要条件,掌握隧道内气温沿进深方向的分布是寒区隧道冻害研究和工程防治措施采取的基础和前提。然而,不同寒区隧道工程的隧址区环境气象、工程结构和交通情况等因素各不相同,导致不同隧道内气温的分布特征存在显著差异。因此,准确地预测和获取寒区隧道内气温纵向分布仍是亟待解决的问题。为得到寒区隧道内气温分布特征及其影响因素,本文采用文献调研和数据统计与分析的方法,收集整理了我国52座寒区隧道内气温的现场监测数据以及相关影响因素数据。依据寒区隧道内气温分布特征,将其划分为对称型、非对称型和贯通型三类,并对各类型寒区隧道的长度和埋深情况进行了统计分析。在此基础上,探讨了隧址区气温和隧道围岩地热以及洞内通风对隧道内气温分布的影响机制,之后针对引起隧道内空气流动的自然风、工程建设、机械通风和交通情况四类因素进行了分析,并指出各类因素的主次影响顺序。研究表明,当隧道两端洞口自然环境要素基本相同且两端洞口高差不大时,隧道内气温往往呈对称型分布;当隧道内存在较大纵坡坡度或受洞外盛行风向影响时,隧道内气温多呈非对称型分布;而当隧道长度较短、埋深小且盛行单向风时,隧道内气温分布常为贯通型。隧址区(隧道进出口)环境气温对隧道内气温分布起决定性作用,隧道埋深状况决定了地热作用从而对洞内气温产生重要影响。通风是影响隧道内气温的关键因素,其中自然风、工程中纵坡设计因素分别为进出口高差较小、长度较短的隧道和进出口高差较大、长度较长的隧道内气温分布的主导因素,工程附属结构、机械通风、交通情况为相对次要因素。本研究工作可为寒区隧道冻害问题研究和保温设防设计以及运营维护提供参考。

Comparison of Several Statistical Analysis Models for Genotypic Stability of Saccharum officinarum

[Objective] The study aimed to compare several statistical analysis models for estimating the sugarcane （Saccharum spp.） genotypic stability. [Method] The data of sugarcane regional trials in Guangdong, in 2009 was analyzed by three models respectively： Finlay and Wilkinson model： the additive main effects and multiplicative interaction （AMMI） model and linear regression-principal components analysis （LR- PCA） model, so as to compare the models. [Result] The Finlay and Wilkinson model was easier, but the analysis of the other two models was more comprehensive, and there was a bit difference between the additive main effects and multiplicative inter- action （AMMI） model and linear regression-principal components analysis （LR-PCA） model. [Conclusion] In practice, while the proper statistical method was usually con- sidered according to the different data, it should be also considered that the same data should be analyzed with different statistical methods in order to get a more reasonable result by comparison.

基于可靠度理论的岩质滑坡稳定性及敏感性分析——以西藏旁多水利枢纽沿线滑坡为例

【目的】研究西藏高海拔地区岩质滑坡的主要失稳机理。【方法】以数学方程中可靠度理论为基础,根据岩质滑坡圆弧滑动稳定性极限特征,结合现场大量试验及数学概率统计,建立其可靠度判定极限状态方程。【结果】研究结果表明:公式中坡度α、坡高H、单位长度滑体的重力W、岩石的黏聚力c、岩石的内摩擦角φ等物理力学参数的均值与变异性系数、可靠度指标存在一定影响规律,并以此建立了岩质滑坡可靠度分析计算模型。【结论】通过各物理力学参数的可靠度敏感性计算分析可知,岩质滑坡的坡度敏感性最高,其次是滑坡的单位长度重力、内摩擦角和黏聚力指标;对于滑坡坡高没有表现出明显的影响规律。

长三角地区AI领域城市协同创新网络及影响因素研究

探索城市协同创新的机制与影响因素,推动地区间与多主体的科技创新发展。本文采集2016—2021年的长三角地区AI(artificial intelligence)领域专利数据,以该地区核心的27座城市作为研究对象,将城市与专利技术知识组合构建城市协同创新网络。采用社会网络分析法对所构建网络的属性特征、离散程度与结构状态及其变化进行分析研究,利用指数随机图模型,结合城市的历年统计指标、城市等级和隶属省份以及历史经验网络,对城市协同创新形成机制与影响因素进行模型构建及分析。研究结果表明,长三角地区AI领域城市协同创新网络的规模和丰富性逐年增长,网络的可达性与影响力逐渐增加,核心城市与技术节点联系紧密、分布在不同子群中且稳定性程度逐渐提高,网络受限节点逐渐减少且结构愈加均衡;在网络形成机制及影响因素方面,节点的主效应中工业化水平和教育支出有明显的促进发展作用,隶属省份与行政等级的同质性对网络发展产生不同的作用,网络路径依赖趋势明显,上一年的现实网络对下一年的网络形成具有重要影响作用。

统计学视角下关中地区西汉墓出土陶仓形制与组合分析

西安地区西汉时期陶仓在形制方面变化并不显著,运用传统方法进行形制分析,所得结论有限。本文引入相关性分析、回归分析、因子分析、聚类分析、均值对比与假设检验等统计学方法对陶仓的数据进行量化分析。结果表明,随时间推移,陶仓整体体形呈先增大后减小的趋势,除新莽时期外均维持在五件一组出土的规格,但出土陶仓的汉墓的比例则一直比较稳定。这与西汉社会经济的发展情况相吻合,同时意味着该时间段内用葬习俗和偏好没有发生明显改变。

山东无棣人工增雨效果的统计检验

为客观评估无棣增雨作业效果,使用1964—2023年滨州、无棣国家级基本气象站及区域气象观测站4—7月降水资料,采用序列分析、区域回归分析、区域对比分析3种统计检验方法对2014—2023年的人工增雨作业效果进行分析研究。结果表明:(1)4—7月序列分析、区域回归分析的旬平均绝对增雨量分别为7.24 mm、7.89 mm;4、5、7月序列分析通过α=0.05的显著性水平检验,4、7月区域回归分析通过α=0.05的显著性水平检验。(2)区域对比分析的作业日平均绝对增雨量为3.75 mm、平均相对增雨率为21.93%;4、6、7月通过α=0.05的显著性水平检验,5月通过α=0.10的显著性水平检验。

不同地区发酵型米酒挥发性风味化合物研究

目的研究不同地区发酵型米酒挥发性风味化合物的特征及地区间关键差异化合物。方法采用顶空固相微萃取与气相色谱-质谱法对米酒主要产区的26个代表性酒样中的挥发性物质进行检测,利用主成分分析和正交偏最小二乘判别分析等多元统计方法进行分析。结果26个酒样中共鉴定出70个主要挥发性风味化合物,包括酯类、醇类、醛类、酸类、烷烃类、酮类及其他类,其中酯类和醇类化合物为主要挥发性成分;根据多元统计分析发现供试酒样呈现出明显的区域特性,日本米酒和中国米酒挥发性风味化合物具有显著差异,日本米酒挥发性风味化合物主要为酯类化合物,包括癸酸乙酯、己酸乙酯、辛酸乙酯、丁酸乙酯、乙酸异戊酯等;国内米酒的挥发性化合物特征与地理位置有一定关系,酒样可区分为2大类,即长江以南(贵州、江西)米酒与长江以北(湖北、江苏)米酒,其中长江以南米酒的特征风味化合物为4-乙基苯酚、乙酸苯乙酯、苯乙醇等芳香族化合物,长江以北米酒的特征风味化合物为辛酸乙酯、香叶醇、辛酸等。结论国内米酒和日本米酒风味的关键差异化合物为己酸乙酯、辛酸乙酯和异戊醇等具有水果甜香的酯类物质及高级醇,国内长江以南和长江以北米酒风味的关键差异化合物为异戊醇、2-甲基丁醇、异丁醇和苯乙醇等高级醇和萜烯醇类物质。

区域环境统计在环境管理中的应用分析

本文简述了环境统计制度的发展历程,并以成武县环境统计数据在该地区的实践应用为例,重点对工业源环境统计数据进行分析;论述了区域环境统计在环境管理中的实际应用领域、方式、意义等,以及目前环境统计制度在基层环境管理实践中遇到的问题及建议。

数理统计方法在湘赣边区域合作示范区建设中的应用——以文化遗产保护与开发为例

红色文化遗产是中华民族宝贵的精神财富,具有重要的历史和文化价值。湘赣边区域是中国革命和中国共产党的重要策源地,该区域红色文化遗产的创新性转化和创造性发展,对该区域的高质量发展具有重要意义。文章通过数理统计方法对红色文化遗产资源保护与开发的研究成果进行系统研究,进而介绍了湘赣边区域红色文化遗产资源开发与利用概况,利用SWOT分析法研究湘赣边区域红色文化遗产资源开发问题,并从多路径提出该区域红色文化遗产资源创新性转化和创造性发展的对策建议,以促进湘赣边区域经济社会可持续发展。

ON CONFIDENCE REGIONS OF SEMIPARAMETRIC NONLINEAR REGRESSION MODELS(A GEOMETRIC APPROACH)

A geometric framework is proposed for semiparametric nonlinear regression models based on the concept of least favorable curve, introduced by Severini and Wong (1992). The authors use this framework to drive three kinds of improved approximate confidence regions for the parameter and parameter subset in terms of curvatures. The results obtained by Hamilton et al. (1982), Hamilton (1986) and Wei (1994) are extended to semiparametric nonlinear regression models.