Fuzzy Clustering Validity for Spatia Data

The validity measurement of fuzzy clustering is a key problem. If clustering is formed, it needs a kind of machine to verify its validity. To make mining more accountable, comprehensible and with a usable spatial pattern, it is necessary to first detect whether the data set has a clustered structure or not before clustering. This paper discusses a detection method for clustered patterns and a fuzzy clustering algorithm, and studies the validity function of the result produced by fuzzy clustering based on two aspects, which reflect the un-certainty of classification during fuzzy partition and spatial location features of spatial data, and proposes a new validity function of fuzzy clustering for spatial data. The experimental result indicates that the new validity function can accurately measure the validity of the results of fuzzy clustering. Especially, for the result of fuzzy clustering of spatial data, it is robust and its classification result is better when compared to other indices.

Snow and sea ice thermodynamics in the Arctic:Model validation and sensitivity study against SHEBA data

Evolution of the Arctic sea ice and its snow cover during the SHEBA year were simulated by applying a high-resolution thermodynamic snow/ice model （HIGHTSI）. Attention was paid to the impact of albedo on snow and sea ice mass balance, effect of snow on total ice mass balance, and the model vertical resolution. The SHEBA annual simulation was made applying the best possible external forcing data set created by the Sea Ice Model Intercomparison Project. The HIGHTSI control run reasonably reproduced the observed snow and ice thickness. A number of albedo schemes were incorporated into HIGHTSI to study the feedback processes between the albedo and snow and ice thickness. The snow thickness turned out to be an essential variable in the albedo parameterization. Albedo schemes dependent on the surface temperature were liable to excessive positive feedback effects generated by errors in the modelled surface temperature. The superimposed ice formation should be taken into account for the annual Arctic sea ice mass balance.

Orthogonal Series Estimation of Nonparametric Regression Measurement Error Models with Validation Data

In this article we study the estimation method of nonparametric regression measurement error model based on a validation data. The estimation procedures are based on orthogonal series estimation and truncated series approximation methods without specifying any structure equation and the distribution assumption. The convergence rates of the proposed estimator are derived. By example and through simulation, the method is robust against the misspecification of a measurement error model.

Estimation of Nonparametric Multiple Regression Measurement Error Models with Validation Data

In this article, we develop estimation approaches for nonparametric multiple regression measurement error models when both independent validation data on covariables and primary data on the response variable and surrogate covariables are available. An estimator which integrates Fourier series estimation and truncated series approximation methods is derived without any error model structure assumption between the true covariables and surrogate variables. Most importantly, our proposed methodology can be readily extended to the case that only some of covariates are measured with errors with the assistance of validation data. Under mild conditions, we derive the convergence rates of the proposed estimators. The finite-sample properties of the estimators are investigated through simulation studies.

The Importance of Integrating Geological Mapping Information with Validated Assay Data for Generating Accurate Geological Wireframes in Orebody Modelling of Mineral Deposit in Mineral Resource Estimation: A Case Study in AngloGold Ashanti, Obuasi Mine

The basis of accurate mineral resource estimates is to have a geological model which replicates the nature and style of the orebody. Key inputs into the generation of a good geological model are the sample data and mapping information. The Obuasi Mine sample data with a lot of legacy issues were subjected to a robust validation process and integrated with mapping information to generate an accurate geological orebody model for mineral resource estimation in Block 8 Lower. Validation of the sample data focused on replacing missing collar coordinates, missing assays, and correcting magnetic declination that was used to convert the downhole surveys from true to magnetic, fix missing lithology and finally assign confidence numbers to all the sample data. The missing coordinates which were replaced ensured that the sample data plotted at their correct location in space as intended from the planning stage. Magnetic declination data, which was maintained constant throughout all the years even though it changes every year, was also corrected in the validation project. The corrected magnetic declination ensured that the drillholes were plotted on their accurate trajectory as per the planned azimuth and also reflected the true position of the intercepted mineralized fissure(s) which was previously not the case and marked a major blot in the modelling of the Obuasi orebody. The incorporation of mapped data with the validated sample data in the wireframes resulted in a better interpretation of the orebody. The updated mineral resource generated by domaining quartz from the sulphides and compared with the old resource showed that the sulphide tonnes in the old resource estimates were overestimated by 1% and the grade overestimated by 8.5%.

由“体验式”到“验证式”:“新文科”背景下法学实验教学的模式优化

“新文科”的内涵可以被解构为学科交叉之新理念、科教融合之新目标与文理交融之新方法;法学实验教学作为法学教育体系中最具实践性、前沿性与创新性的环节,应当及时回应上述新诉求。目前,法学实验教学模式仍表现出“体验式”路径依赖,即便是融入科技元素的虚拟仿真也是以体验各类诉讼程序或非诉流程为目标,未能体现出“假设与验证”的实验教学本质。将类案司法裁判文书作为大数据素材,有助于在法学教育中融入计算科学的思维与方法,以一种科学发现的姿态去探索与验证所学法学理论,呈现法学实验教学的“验证式”面孔。依托于“构想提出、确立假设、文书检索、数据分析、理论检验与方法总结”等核心环节,可以确立“验证式”法学实验教学方案。

Statistical Tests of the Validation of TCO Satellite Measurements, Recorded Simultaneously by TOMS-OMI (2005) and OMI-OMPS (2012-2018)

Two statistical validation methods were used to evaluate the confidence level of the Total Column Ozone (TCO) measurements recorded by satellite systems measuring simultaneously, one using the normal distribution and another using the Mann-Whitney test. First, the reliability of the TCO measurements was studied hemispherically. While similar coincidences and levels of significance > 0.05 were found with the two statistical tests, an enormous variability in the levels of significance throughout the year was also exposed. Then, using the same statistical comparison methods, a latitudinal study was carried out in order to elucidate the geographical distribution that gave rise to this variability. Our study reveals that between the TOMS and OMI measurements in 2005 there was only a coincidence in 50% of the latitudes, which explained the variability. This implies that for 2005, the TOMS measurements are not completely reliable, except between the -50° and -15° latitude band in the southern hemisphere and between +15° and +50° latitude band in the northern hemisphere. In the case of OMI-OMPS, we observe that between 2011 and 2016 the measurements of both satellite systems are reasonably similar with a confidence level higher than 95%. However, in 2017 a band with a width of 20° latitude centered on the equator appeared, in which the significance levels were much less than 0.05, indicating that one of the measurement systems had begun to fail. In 2018, the fault was not only located in the equator, but was also replicated in various bands in the Southern Hemisphere. We interpret this as evidence of irreversible failure in one of the measurement systems.

数据确权协商机制的构建——基于生成场景的多元化

作为新型生产要素,数据的重要性不言而喻,但权属不清或产权不明影响数据效能发挥,阻碍数字经济发展。就概念界定而言,数据是信息的载体和表现形式,二者通过数字技术相互联结、相互贯通。现行规则下,无论是物权法模式,还是知识产权法模式,抑或是竞争法模式,都存在明显弊端,实不足取。究其根本,数据是一种生成品,其生成场景表现出多元化特征。鉴于此,数据产权应当归数据来源者和处理者等参与数据生成的主体所有,并且可以通过构建分散式、低成本的协商机制加以确定。与此同时,为保证确权协议格式条款的协商属性,宜对数据进行分类分级。一方面,以数据来源者为标准,将数据分为个人数据、企业数据以及公共数据;另一方面,以数据安全风险为标准,将数据分为由低风险至高风险的五级数据。

基于数据影响的业务流程一致性检查方法

近年来,业务流程的精确管理受到越来越多的关注,作为业务流程管理内容之一的一致性检查技术正变得越来越重要。现有的一致性检查技术主要从模型的控制流角度出发,并未考虑业务流程中的数据或数据的变化对业务流程产生的影响,为此提出了一种基于数据影响的业务流程一致性检查方法。首先,通过业务流程建模符号(business process modeling notation,BPMN)模型中数据和行为之间的依赖关系来分析数据对偏差活动预期行为的影响,进而获取偏差活动的预期行为集;其次,通过在BPMN模型中引入决策模型和符号(decision model and notation,DMN)决策表来充分捕获当前实例执行的数据上下文与行为上下文之间的关系,以区分有效数据更改和异常数据更改,找到偏差活动的有效预期行为集。最后,通过设计数据对偏差活动影响的各类成本函数提出了有效一致性检查方法。实验结果表明,相比已有工作,该方法在进行业务流程一致性检查时提高了业务流程的一致性,可以成功捕获偏差活动作出反应的适应行为,使得业务流程在复杂多变的环境下表现得更加准确、合理。

智慧城市运营能力及其影响要素的分析和研究——以石家庄为例

回顾智慧城市运营能力发展的历史阶段,并探讨未来的发展趋势,即自动驾驶和无人驾驶阶段。此外,以石家庄为例通过问卷调查和数据分析,讨论交通管理、能源利用和基础设施建设等能力要素对智慧城市运营能力的影响。这些分析有助于我们更好地理解智慧城市运营能力的现状和发展方向,为未来的城市规划提供参考。

我国大型社会调查的经验与反思

大型社会调查既为社会变迁的现状和趋势分析积累了宝贵的数据,又为教学、科研和公共决策提供了重要参考。21世纪以来,大型社会调查在抽样技术、管理模式、访问执行和数据分析等方面不断积累经验,为数据使用者提供高质量的数据库。本文在总结这些经验的基础上,从测量的视角进行反思,以跨情境效度、概念规范性、比照权威统计为切入点,以典型概念的测量和数据分析为例子,从调查方法层面总结调查研究如何推动社会议题的发展。

基于分段特征提取的仿真模型结果验证方法

校核、验证与确认(verification,validation,and accreditation,VV&A)是保证仿真模型可信度的关键手段,其中模型验证是核心环节。针对导弹飞行仿真模型结果验证存在的参考数据不可获得、参考数据来源多样、专家验证主观性强等问题,提出一种基于时间序列分段特征提取的导弹飞行仿真模型结果验证方法。提出了一种综合的时间序列分段线性方法,由基于二阶导数提取趋势边缘点的线性分段算法和基于极值点优化的Top-Down线性分段算法两部分组成,以实现对导弹飞行仿真数据和参考数据进行有效的线性分段表示。基于上述分段结果,对各段时间序列的均值、方差、斜率等特征进行提取,以辅助专家进行验证,从而降低验证中的主观性;或者直接利用TIC系数法、动态时间规整(dynamic time warping,DTW)等方法进行客观的相似性分析。通过充分利用时间序列的分段特征,可实现各种情形下的导弹飞行仿真模型结果验证。通过一个导弹模型结果验证案例演示了所提方法的可行性和有效性。

基于水文变异特征的石臼湖生态水位及保障度研究

石臼湖作为长江下游的通江湖泊,逐步形成了独具特色的河流湖泊复合生态系统,研究其生态水位对于保障湖泊生物多样性具有重要意义。利用蛇山水位站1973—2020年日均水位过程,分析石臼湖的水位变异特征,结合年保证率法和年内展布法得到逐月最低生态水位,并对水位突变前后的生态水位保障度进行研究,相关成果可为维护石臼湖水生生态系统结构和功能提供数据参考。

Oracle GoldenGate Veridata数据验证技术的研究与应用

在企业数据中心、灾备中心的建设中广泛采用数据同步复制技术和数据异步复制技术来得到共享数据或灾备数据,许多原因会导致复制两端数据不一致而又很难及时发现。这些不一致会导致采用不准确的数据进行数据恢复和基于不准确数据的企业决策。通过引入Oracle GoldenGate Veridata数据验证技术,可以实现在线校验在不同应用之间共同使用的大量数据,确保数据绝对可信,找到可以常态化的数据一致性、完整性验证方法。

基于编码标准的Geodatabase设计

地理要素的分类代码信息通常以主代码和辅代码的不同组合模式来表达。在地理信息数据库(Geodata-base)数据模型中,以国家标准地理信息分类代码体系为基础,在数据字典表中存储地理要素实体的分类与特征属性,利用有效值表将地理要素与其本身的代码信息联系起来。在ArcGIS应用程序平台下实现对地理数据的管理和应用,从而更加详细、准确地表达地理要素的含义。

计算机英语词汇管理Validator框架数据校验

建立词汇管理系统是解决计算机词汇增长过快、难于学习和使用的有效途径,本文基于Validator框架研究数据输入检验,为系统开发提供支持。首先,研究了Validator框架的构成并对各部件进行了简要描述;然后,基于My SQL数据库管理系统设计了词汇存储数据结构;最后,按照建立validation.xml配置文件、在struts-config.xml中配置Validator插件、修改Action Form的父类、配置Validator调用等步骤完成了数据校验。本文的研究方法具有配置简单、使用方便等特点。

基于熵的微阵列数据特征选择

针对基于熵的特征加权算法忽略了数据集内在特性对特征重要性的影响,导致特征选择效果不佳的问题,提出一种改进的基于熵的特征加权算法,根据信息熵计算特征维度的重要性权重,通过引入交叉验证实现不同数据集的阈值学习,确定用于度量特征重要性的最佳阈值参数,并基于该阈值对数据集进行特征选择。在微阵列数据集上的数值实验结果表明:相比于原算法,所提算法能够减少更多的维度,且特征子集用于分类得到的准确率与原算法基本持平甚至有所提高,说明改进的算法是可行和有效的。

基于AdaBoost算法的混凝土抗压强度预测

论文采集1030组混凝土抗压强度试验数据,通过训练AdaBoost算法,得到可用于预测混凝土抗压强度值的模型。结果表明:AdaBoost算法模型可以在给定输入变量的情况下准确有效地预测混凝土抗压强度;10折交叉验证决定系数R2的平均值达到0.952,平均绝对百分比误差(MAPE)达到11.39%,说明十折交叉验证具有较高准确率;AdaBoost算法与人工神经网络和支持向量机独立学习算法比较,表现出集成学习算法的优越性;讨论了AdaBoost算法模型中训练数据集数量、弱学习器类型和输入变量的数量相关因素,发现使用1030数据集的80%可以获得良好的预测结果。

基于大数据驱动的高职专业认证研究

高职专业认证事关高职教育的高质量发展全局,是助推职业教育内涵式发展的重要抓手。大数据技术中的多源数据融合技术、智能推荐算法技术、数据计算技术与高职专业认证的数据获取、体系完善、结果反馈及应用具有极大的联系性,满足高职专业认证客观化、精准化和科学化发展的现实需要。但大数据技术驱动高职专业认证可能引发伦理性问题、主体性困境和失真性风险三大问题。为此,应建立智能认证规章制度,规范认证行为;多元创新专业认证观念,校正认证方向;增强技术赋能的适切性,提升认证效能。