Classification of valence changes of trivalent rare earth ions in alkaline earth borates using artificial neural networks

The investigations of classification on the valence changes from RE3+ to RE2+ (RE = Eu, Sm, Yb, Tm) in host compounds of alkaline earth berate were performed using artificial neural networks (ANNs). For comparison, the common methods of pattern recognition, such as SIMCA, KNN, Fisher discriminant analysis and stepwise discriminant analysis were adopted. A learning set consisting of 24 host compounds and a test set consisting of 12 host compounds were characterized by eight crystal structure parameters. These parameters were reduced from 8 to 4 by leaps and bounds algorithm. The recognition rates from 87.5 to 95.8% and prediction capabilities from 75.0 to 91.7% were obtained. The results provided by ANN method were better than that achieved by the other four methods. (C) 1999 Elsevier Science B.V. All rights reserved.

MULTIVARIATE CLASSIFICATION BASED ON METAL CONTENTS IN HUMAN SENILE CATARACT LENSES

Multivariate classification methods were used to evaluate data on the concentrations of eight metals in human senile lenses measured by atomic absorption spectrometry. Principal components analysis and hierarchical clustering separated senile cataract lenses, nuclei from cataract lenses, and normal lenses into three classes on the basis of the eight elements. Stepwise discriminant analysis was applied to give discriminant functions with five selected variables. Results provided by the linear learning machine method were also satisfactory; the k-nearest neighbour method was less useful.

中太平洋海区富钴结壳地球化学特征及成因机制

本文利用ICP-AES、EPMA、X-ray衍射等测试技术以及聚类分析和因子分析等多种数理统计方法，系统地对中太平洋海区富钴结壳的元素地球化学特征、矿物组成和微观组构进行了研究，并探讨了其成因机制，获得以下主要认识： 1中太平洋海区富钴结壳类型多样，均为水成成因，其矿物相主要由锰矿物相、铁矿物相和非金属矿物相组成；富钴结壳壳层发育多种原生和次生构造类型。 2磷酸盐化作用不仅强烈改变富钴结壳元素初始含量，而且造成富钴结壳某些元素间的相关性发生改变，这些敏感型元素对可用于指示富钴结壳是否发生磷酸盐化。在不同水深段内，未磷酸盐化型富钴结壳的主要元素随经向、纬向的变化趋势相似，表明其受水体化学障、表面生产力和物质来源等环境参数控制；而随水深的变化则具有区域一致性，表明水体化学具有区域成层性。 3未磷酸盐化富钴结壳稀土元素含量和轻重稀土分馏程度随水深发生规律变化，这种变化不仅与它们在海洋中的含量和行为有关，也与海洋背景颗粒的吸附有关；铈(Ce)在富钴结壳中基本上呈4价，且动力学因素控制了其富集过程，因此Ce异常不能用于指示富钴结壳形成环境的氧化程度。 4基于富钴结壳微层呈锯齿状且同一微层生长速率不同，提出了富钴结壳在各种基底表面生长以及后继发育过程受固液界面双电层控制的发育模式。在富钴结壳整个发育过程中，经历了从贫氧环境向富氧环境的转变，但微环境则呈富氧-低氧过程的交替。 关键词： 富钴结壳；中太平洋；元素地球化学；界面双电层

改进的统计不相关最优鉴别矢量集

该文对统计不相关最优鉴别矢量集算法进行研究,在分析统计不相关最优鉴别矢量集算法的基础上提出了一种改进的方法。该方法在类内散布矩阵的特征空间中求解统计不相关最优鉴别矢量集。为了加快特征抽取速度,利用基于图像鉴别分析的维数压缩方法,对图像数据进行了压缩。在ORL和Yale人脸数据库的数值实验,验证本文所提出的方法的有效性。

渤海海域河流相油藏精细描述技术及应用研究

Aiming at the character of Bohaii Sea area and the heterogeneity of fluvial facies reservoir, litho-geophysics experiments and integrated research of geophysical technologies are carried out. To deal with practical problems in oil fields of Bohai area, such as QHD32-6, Southern BZ25-1 and NP35-2 et al., technology of reservoir description based on seismic data and reservoir geophysical methods is built. In this dissertation, three points are emphasized: ①the integration of multidiscipline; ②the application of new methods and technologies; ③the integration of quiescent and dynamic data. At last, research of geology modeling and reservoir numerical simulation based on geophysical data are integrated. There are several innovative results and conclusion in this dissertation: (1)To deal with problems in shallow sea area where seismic data is the key data, a set of technologies for fine reservoir description based on seismic data in Bohai Sea area are built. All these technologies, including technologies of stratigraphic classification, sedimentary facies identification, structure fine characterization, reservoir description, fluid recognition and integration of geological modeling& reservoir numerical simulation, play an important role in the hydrocarbon exploration and development. In the research of lithology and hydrocarbon-bearing condition, petrophysical experiment is carried out. Outdoors inspection and experiment test data are integrated in seismic forward modeling& inversion research. Through the research, the seismic reflection rules of fluid in porosity are generated. Based on all the above research, seismic data is used to classify rock association, identify sedimentary facies belts and recognition hydrocarbon-bearing condition of reservoir. In this research, the geological meaning of geophysical information is more clear and the ambiguity of geophysical information is efficiently reduced, so the reliability in hydrocarbon forecasting is improved. The methods of multi-scales are developed in microfacies research aiming at the condition of shallow sea area in Bohai Sea: ① make the transformation from seismic information to sedimentary facies reality by discriminant analysis; ②in research of planar sedimentary facies, make microfacies research on seismic scale by technologies integration of seismic multi-attributes analysis& optimization, strata slicing and seismic waveform classification; ③descript the sedimentary facies distribution on scales below seismic resolution with the method of stochastic modeling. In the research of geological modeling and reservoir numerical simulation, the way of bilateral iteration between modeling and numerical simulation is carried out in the geological model correction. This process include several steps: ①make seismic forward modeling based on the reservoir numerical simulation results and geological models; ②get trend residual of forward modeling and real seismic data; ③make dynamic correction of the model according to the above trend residual. The modern integration technology of reservoir fine description research in Bohai Sea area, which is developed in this dissertation, is successfully used in (1)the reserve volume evaluation and development research in BZ25-1 oil field and (2)the tracing while drilling research in QHD32-6 oil field. These application researches show wide application potential in hydrocarbon exploration and development research in other oil fields.

陕北桥镇油田延长组长2、长1油层组沉积相及储层研究

The Ordos Basin is a large-scale craton superimposed basin locating on the west of the North China platform, which was the hotspot of interior basin exploration and development. Qiaozhen oil field located in the Ganquan region of south-central of Ordos Basin. The paper is based on the existing research data, combined with the new theory and progress of the sedimentology, sequence stratigraphy, reservoir sedimentology, petroleum geology, etc, and analyzes systematically the sedimentary and reservoir characteristics in the chang2 and chang1 oil-bearing strata group of Yanchang formation On the basis of stratigraphic classification and comparison study, the strata chang2 and chang1 were divided into five intervals. Appling the method of cartography with single factor and dominance aspect, we have drawn contour line map of sand thickness, contour line map of ratio between sand thickness and stratum thickness. We discussed distribution characteristics of reservoir sand body and evolution of sedimentary facies and microfacies. And combining the field type section , lithologic characteristics, sedimentary structures, the sedimentary facies of single oil well and particle size analysis and according to the features of different sequence, the study area was divided into one sedimentary facies、three parfacies and ten microfacies. The author chew over the characteristics of every facies, parfacies and microfacies and spatial and temporal distribution. Comprehensive research on petrologic characteristics of reservoir , diagenesis types, pore types, distribution of sand bodies, physical properties, oiliness, reservoir heterogeneities, characteristics of interlayer, eventually research on synthetic classifying evaluation of reservoir.The reservoir is classified four types: Ⅰ、Ⅱ、Ⅲ、Ⅳ and pore type, fracture-porosity type. Take reservoir's average thickness, porosity, permeability, oil saturation and shale content as parameters, by using clustering analysis and discriminant analysis, the reservoir is classified three groups. Based on the evaluation, synthetizing the reservoir quality, the sealing ability of cap rock, trap types, reservoir-forming model ,in order to analyze the disciplinarian of accumulation oil&gas. Ultimately, many favorable zones were examined for chang23，chang223，chang222，chang221，chang212，chang12，chang11 intervals. There are twenty two favorable zones in the research area. Meanwhile deploy the next disposition scheme.

社会形势预警的几种建模方法比较

Based on social survey data conducted by local research group in some counties executed in the nearly past five years in China, the author proposed and solved two kernel problems in the field of social situation forecasting: i) How can the attitudes’ data on individual level be integrated with social situation data on macrolevel; ii) How can the powers of forecasting models’ constructed by different statistic methods be compared? Five integrative statistics were applied to the research: 1) algorithm average (MEAN); 2) standard deviation (SD); 3) coefficient variability (CV); 4) mixed secondary moment (M2); 5) Tendency (TD). To solve the former problem, the five statistics were taken to synthesize the individual and mocrolevel data of social situations on the levels of counties’ regions, and form novel integrative datasets, from the basis of which, the latter problem was accomplished by the author: modeling methods such as Multiple Regression Analysis (MRA), Discriminant Analysis (DA) and Support Vector Machine (SVM) were used to construct several forecasting models. Meanwhile, on the dimensions of stepwise vs. enter, short-term vs. long-term forecasting and different integrative (statistic) models, meta-analysis and power analysis were taken to compare the predicting power of each model within and among modeling methods. Finally, it can be concluded from the research of the dissertation: 1) Exactly significant difference exists among different integrative (statistic) models, in which, tendency (TD) integrative models have the highest power, but coefficient variability (CV) ones have the lowest; 2) There is no significant difference of the power between stepwise and enter models as well as short-term and long-term forecasting models; 3) There is significant difference among models constructed by different methods, of which, support vector machine (SVM) has the highest statistic power. This research founded basis in all facets for exploring the optimal forecasting models of social situation’s more deeply, further more, it is the first time methods of meta-analysis and power analysis were immersed into the assessments of such forecasting models.

不同行业的企业形象要素体系的共性与个性

In the early part of this century, with the change from the seller's market to the buyer market, the competition between companies changed from product competition, selling competition to corporate image competition, and companies began to consciously build corporate reputation through fast developed mass media. As a result, a series of methods to build corporate image were created, such as advertising, public relations and corporate identify system(CIS), which ,in turn, promoted the development of the research of corporate image. The factors of corporate image have been the central issue of the corporate image research, for the probe of this issue is of great significance to both the development of corporate image theory and the practice of corporate image building. As far as the literature we have gathered is concerned, the exiting research on this topic either remains at the level of qualitative investigating and induction, or is limited in some particular industry. Therefore. There bean no commonly accepted corporate image theory so far. In the recent years, with the introduction of competition mechanism and the establishment of the company. As subject position in the market, the building of corporate image gas been developed quickly in our country, and the development of practice imperatively requires the guide of scientific theory. On the basis of the analysis and summarization of the research of the predecessors, the present dissertation attempts to do some investigation and research work on the common and individual characteristics of corporate image factors of the companies in different industries in our country. The method of questionnaire survey is used in the present research. The subject sample is gathered on the basis of convenience and feasibility, and at the mean time, some consideration is also given to straticulate randomization principles. The subjects are asked to select one of their most familiar companies, and determine the important of even item in the questionnaire to the selected company(i.e. the importance assessment), and then, determine the grades the selected company gains on every item(i.e. the image assessment). The discriminant analysis of corporate image of different industries. The selected sample is grouped and coded according to the standard of industry classification. The discriminant analysis is done with the selected companies as the sample and the grades of image assessment as the variables. The result indicates that industry variable is an important standard of the classification of corporate image, and the companies in the same industry are more similar in corporate image. The analysis of the common and individual characteristics of corporate image of different industries. Firstly, in every industry, the items are sieved according to the grades of importance assessment, and exploratory factor analysis is done with grades of image assessment on the selected items as the variables. Secondly, the factors drawn from every industry in arranged in order according to their importance. The result indicates that the corporate image of different industries shares some common characteristics, for there exist common factors among different industries. In the mean while, the corporate image of different industries has its individual characteristics, that is, there is some difference in the domain of the factors, and in the order of the factors(including the difference of the principle factor).

判别分析系统应运于生物标本鉴定的初步研究

计算机技术和数学方法、手段应用于生物标本鉴定的研究工作在国外开展已有多年，但在国内却并没有许多人涉猎，也没有受到足够的重视。 鉴于这一领域的重要性及其实际意义，本文综合、扩充、改进了多元统计判别分析和模糊模式识别中的多种定量化判别方法，初步在计算机上实现了一个可用于生物标本鉴定或其它与判别、识别有关方面的系统，并将其用于桔梗科沙参属三个种：泡沙参、多歧沙参和裂叶沙参及菖蒲科中两个种的标本鉴定上面，获得了比较满意的判别效果。同时，为了弥补数量化标本鉴定的不足，本文作者还设计开发了一个描述性的基于检索表的人机交互式的标本鉴定模块。另外，本系统还包括模糊系统聚类和典型相关分析等模块，可供生物分类及其它定量分析运算时选用。 对于以上各种判别、识别方法的差异及优劣，文中根据实例做出了综合分析和比较，并认为在所有方法当中，逐步判别法和模糊协方差识别法最适宜于生物标本鉴定之用。最后，作者展望了未来计算机用于生物标本鉴定的前景。

近邻边界Fisher判别分析

将数据集进行合理的维数约简对于一些机器学习算法效率的提高起着至关重要的影响.该文提出了一种利用数据点邻域信息的线性监督降维算法:近邻边界Fisher判别分析(Neighborhood Margin Fisher Discriminant Analysis,NMFDA).NMFDA尝试将每一数据点邻域内最远的同类数据点和最近的异类数据点之间的边界在投影子空间内尽可能地扩大,从而提高基于距离的识别算法的准确率.同时为了解决非线性降维问题,提出了Kernel NMFDA,通过在几个标准人脸数据库上与其它降维算法的对比识别实验,验证了提出算法的有效性.

Cross-correlation between WMAP and 2MASS: non-Gaussianity induced by the SZ effect

We study the non-Gaussianity induced by the Sunyaev-Zel'dovich (SZ) effect in cosmic microwave background (CMB) fluctuation maps. If a CMB map is contaminated by the SZ effect of galaxies or galaxy clusters, the CMB maps should have similar non-Gaussian features to the galaxy and cluster fields. Using the WMAP data and 2MASS galaxy catalogue, we show that the non-Gaussianity of the 2MASS galaxies is imprinted on WMAP maps. The signature of non-Gaussianity can be seen with the fourth-order cross-correlation between the wavelet variables of the WMAP maps and 2MASS clusters. The intensity of the fourth-order non-Gaussian features is found to be consistent with the contamination of the SZ effect of 2MASS galaxies. We also show that this non-Gaussianity can not be seen by the high-order autocorrelation of the WMAP. This is because the SZ signals in the autocorrelations of the WMAP data generally are weaker than the WMAP-2MASS cross-correlations by a factor f(2), which is the ratio between the powers of the SZ-effect map and the CMB fluctuations on the scale considered. Therefore, the ratio of high-order autocorrelations of CMB maps to cross-correlations of the CMB maps and galaxy field would be effective to constrain the powers of the SZ effect on various scales.

广义统计不相关最优鉴别矢量集的一个理论结果

本文对统计不相关最优鉴别矢量集的理论问题进行研究 ,提出了广义统计不相关最优鉴别准则 ,并给出了广义统计不相关最佳鉴别矢量集的一个理论结果 ,研究表明 ,广义统计不相关最佳鉴别矢量集的计算公式与基于Fisher最优鉴别准则的统计不相关最佳鉴别矢量集的计算公式完全一样 ,但是以前这一点没有被认识到 .本文的研究丰富了统计不相关最优鉴别分析的特征抽取理论 .

基于模糊神经网络的人脸识别方法研究

人脸识别是模式识别研究领域的重要课题,具有广阔的应用前景。本文提出了基于模糊神 经网络的人脸识别方法。首先用最优鉴别分析方法提取人脸的最优鉴别矢量集,构成特征空间,然后在 特征空间中设计模糊神经网络分类器。在ORL人脸图象库上的实验结果表明了该方法的有效性。

Geographic variation of the Perny's Long-nosed squirrels (Dremomys pernyi) (Milne-Edwards, 1867) (Rodentia : Sciuridae) from southwestern China based on cranial morphometric variables

A sample of 114 specimens of Dremomys pernyi was investigated, 73 of which had intact skulls and were subjected to multivariate, coefficient of difference (C. D.), and cluster analyses. Results indicate that 4 subspecies (groups) of Dremomys pernyi inhabi

Packing LUT clusters with network flow programming

This paper describes a two-step packing algorithm for LUT clusters of which the LUT input multipliers are depopulated. In the first step, a greedy algorithm is used to search for BLE locations and cluster inputs. If the greedy algorithm fails, the second step with network flow programming algorithm is employed. Numerical results illustrate that our two-step packing algorithm obtains better packing density than one-step greedy packing algorithm.