The current GIS can only deal with 2-D or 2.5-D information on the earth surface. A new 3-D data structure and data model need to be designed for the 3-D GIS. This paper analyzes diverse 3-D spatial phenomena from min...The current GIS can only deal with 2-D or 2.5-D information on the earth surface. A new 3-D data structure and data model need to be designed for the 3-D GIS. This paper analyzes diverse 3-D spatial phenomena from mine to geology and their complicated relations, and proposes several new kinds of spatial objects including cross-section, column body and digital surface model to represent some special spatial phenomena like tunnels and irregular surfaces of an ore body. An integrated data structure including vector, raster and object-oriented data models is used to represent various 3-D spatial objects and their relations. The integrated data structure and object-oriented data model can be used as bases to design and realize a 3-D geographic information system.展开更多
To solve the unbalanced data problems of learning models for semantic concepts, an optimized modeling method based on the posterior probability support vector machine （PPSVM） is presented. A neighborbased posterior ...To solve the unbalanced data problems of learning models for semantic concepts, an optimized modeling method based on the posterior probability support vector machine （PPSVM） is presented. A neighborbased posterior probability estimator for visual concepts is provided. The proposed method has been applied in a high-level visual semantic concept classification system and the experiment results show that it results in enhanced performance over the baseline SVM models, as well as in improved robustness with respect to high-level visual semantic concept classification.展开更多
The purpose of this paper is to study the theory of conservative estimating functions in nonlinear regression model with aggregated data. In this model, a quasi-score function with aggregated data is defined. When thi...The purpose of this paper is to study the theory of conservative estimating functions in nonlinear regression model with aggregated data. In this model, a quasi-score function with aggregated data is defined. When this function happens to be conservative, it is projection of the true score function onto a class of estimation functions. By constructing, the potential function for the projected score with aggregated data is obtained, which have some properties of log-likelihood function.展开更多
Molten iron temperature as well as Si, P, and S contents is the most essential molten iron quality （MIQ） indices in the blast furnace （BF） ironmaking, which requires strict monitoring during the whole ironmaking p...Molten iron temperature as well as Si, P, and S contents is the most essential molten iron quality （MIQ） indices in the blast furnace （BF） ironmaking, which requires strict monitoring during the whole ironmaking production. However, these MIQ parameters are difficult to be directly measured online, and large-time delay exists in off-line analysis through laboratory sampling. Focusing on the practical challenge, a data-driven modeling method was presented for the prediction of MIQ using the improved muhivariable incremental random vector functional-link net- works （M-I-RVFLNs）. Compared with the conventional random vector functional-link networks （RVFLNs） and the online sequential RVFLNs, the M-I-RVFLNs have solved the problem of deciding the optimal number of hidden nodes and overcome the overfitting problems. Moreover, the proposed M I RVFLNs model has exhibited the potential for multivariable prediction of the MIQ and improved the terminal condition for the multiple-input multiple-out- put （MIMO） dynamic system, which is suitable for the BF ironmaking process in practice. Ultimately, industrial experiments and contrastive researches have been conducted on the BF No. 2 in Liuzhou Iron and Steel Group Co. Ltd. of China using the proposed method, and the results demonstrate that the established model produces better estima ting accuracy than other MIQ modeling methods.展开更多
Complex industry processes often need multiple operation modes to meet the change of production conditions. In the same mode,there are discrete samples belonging to this mode. Therefore,it is important to consider the...Complex industry processes often need multiple operation modes to meet the change of production conditions. In the same mode,there are discrete samples belonging to this mode. Therefore,it is important to consider the samples which are sparse in the mode.To solve this issue,a new approach called density-based support vector data description( DBSVDD) is proposed. In this article,an algorithm using Gaussian mixture model( GMM) with the DBSVDD technique is proposed for process monitoring. The GMM method is used to obtain the center of each mode and determine the number of the modes. Considering the complexity of the data distribution and discrete samples in monitoring process,the DBSVDD is utilized for process monitoring. Finally,the validity and effectiveness of the DBSVDD method are illustrated through the Tennessee Eastman( TE) process.展开更多
质量相关故障诊断是当前过程控制领域的研究热点之一,然而过程变量与质量变量间的复杂关系使得故障检测性能提升和可视化呈现面临严峻挑战。为此,提出了一种新的质量相关故障诊断方法和故障量化评估准则。首先,基于提升树模型解析过程...质量相关故障诊断是当前过程控制领域的研究热点之一,然而过程变量与质量变量间的复杂关系使得故障检测性能提升和可视化呈现面临严峻挑战。为此,提出了一种新的质量相关故障诊断方法和故障量化评估准则。首先,基于提升树模型解析过程变量与质量变量间的关联,并根据提升树模型的3个特性定义特征重要性分数。然后,将特征重要性分数应用于支持向量数据描述的权衡参数中,构建特征重要性正则化的支持向量数据描述(Feature Importance Regularized Support Vector Data Description, FIR-SVDD)。最后,在核空间中利用投影球面距离度量进行故障量化评估。采用田纳西-伊斯曼化工数据和HYDAC液压系统数据进行对比实验,结果表明所提方法具有更好的性能。展开更多
【目的】全球离散格网系统(Discrete Global Grid Systems,DGGS)本质上是多尺度栅格结构,地理空间矢量与格网的集成是难点,矢量线格网化是其中的基本问题。现有方案多以平面格网单元中心(格心)连线为矢量线建模结果,但扩展到球面后建模...【目的】全球离散格网系统(Discrete Global Grid Systems,DGGS)本质上是多尺度栅格结构,地理空间矢量与格网的集成是难点,矢量线格网化是其中的基本问题。现有方案多以平面格网单元中心(格心)连线为矢量线建模结果,但扩展到球面后建模精度降低,本文针对这一缺陷提出矢量线全球离散格网系统高精度建模方法。【方法】首先选择与地球拟合程度更高的菱形三十面体构建六边形格网系统,以3个相邻菱形面构成组合结构并建立三轴整数坐标系描述单元空间位置;然后根据矢量线首尾端点所在单元确定最优方向编码以减少搜索范围,通过编码邻近运算搜索矢量线经过的球面单元,以球面格心连线为建模结果并提出跨面矢量线处理方法;最后增加单元顶点(格点)作为结构要素,实现多结构要素矢量线建模,进一步提高建模精度。【结果】实验结果表明:本文方案能正确实现全球各个大洲海岸线格网化建模,确保格网化单元与矢量线拓扑相交,且相较平面格网建模结果兼具精度和效率优势。【结论】针对传统矢量数据格网建模方法的几何精度损失和拓扑畸变问题,本文提出高精度球面格网化建模方法,为矢量数据转换至格网同构处理提供有力支撑。展开更多
基金Project supported by the National Natural Science Foundation of China (No.49871066)
文摘The current GIS can only deal with 2-D or 2.5-D information on the earth surface. A new 3-D data structure and data model need to be designed for the 3-D GIS. This paper analyzes diverse 3-D spatial phenomena from mine to geology and their complicated relations, and proposes several new kinds of spatial objects including cross-section, column body and digital surface model to represent some special spatial phenomena like tunnels and irregular surfaces of an ore body. An integrated data structure including vector, raster and object-oriented data models is used to represent various 3-D spatial objects and their relations. The integrated data structure and object-oriented data model can be used as bases to design and realize a 3-D geographic information system.
基金Sponsored by the Beijing Municipal Natural Science Foundation(4082027)
文摘To solve the unbalanced data problems of learning models for semantic concepts, an optimized modeling method based on the posterior probability support vector machine （PPSVM） is presented. A neighborbased posterior probability estimator for visual concepts is provided. The proposed method has been applied in a high-level visual semantic concept classification system and the experiment results show that it results in enhanced performance over the baseline SVM models, as well as in improved robustness with respect to high-level visual semantic concept classification.
文摘The purpose of this paper is to study the theory of conservative estimating functions in nonlinear regression model with aggregated data. In this model, a quasi-score function with aggregated data is defined. When this function happens to be conservative, it is projection of the true score function onto a class of estimation functions. By constructing, the potential function for the projected score with aggregated data is obtained, which have some properties of log-likelihood function.
基金Item Sponsored by National Natural Science Foundation of China(61290323,61333007,61473064)Fundamental Research Funds for Central Universities of China(N130108001)+1 种基金National High Technology Research and Development Program of China(2015AA043802)General Project on Scientific Research for Education Department of Liaoning Province of China(L20150186)
文摘Molten iron temperature as well as Si, P, and S contents is the most essential molten iron quality （MIQ） indices in the blast furnace （BF） ironmaking, which requires strict monitoring during the whole ironmaking production. However, these MIQ parameters are difficult to be directly measured online, and large-time delay exists in off-line analysis through laboratory sampling. Focusing on the practical challenge, a data-driven modeling method was presented for the prediction of MIQ using the improved muhivariable incremental random vector functional-link net- works （M-I-RVFLNs）. Compared with the conventional random vector functional-link networks （RVFLNs） and the online sequential RVFLNs, the M-I-RVFLNs have solved the problem of deciding the optimal number of hidden nodes and overcome the overfitting problems. Moreover, the proposed M I RVFLNs model has exhibited the potential for multivariable prediction of the MIQ and improved the terminal condition for the multiple-input multiple-out- put （MIMO） dynamic system, which is suitable for the BF ironmaking process in practice. Ultimately, industrial experiments and contrastive researches have been conducted on the BF No. 2 in Liuzhou Iron and Steel Group Co. Ltd. of China using the proposed method, and the results demonstrate that the established model produces better estima ting accuracy than other MIQ modeling methods.
基金National Natural Science Foundation of China(No.61374140)the Youth Foundation of National Natural Science Foundation of China(No.61403072)
文摘Complex industry processes often need multiple operation modes to meet the change of production conditions. In the same mode,there are discrete samples belonging to this mode. Therefore,it is important to consider the samples which are sparse in the mode.To solve this issue,a new approach called density-based support vector data description( DBSVDD) is proposed. In this article,an algorithm using Gaussian mixture model( GMM) with the DBSVDD technique is proposed for process monitoring. The GMM method is used to obtain the center of each mode and determine the number of the modes. Considering the complexity of the data distribution and discrete samples in monitoring process,the DBSVDD is utilized for process monitoring. Finally,the validity and effectiveness of the DBSVDD method are illustrated through the Tennessee Eastman( TE) process.
文摘质量相关故障诊断是当前过程控制领域的研究热点之一,然而过程变量与质量变量间的复杂关系使得故障检测性能提升和可视化呈现面临严峻挑战。为此,提出了一种新的质量相关故障诊断方法和故障量化评估准则。首先,基于提升树模型解析过程变量与质量变量间的关联,并根据提升树模型的3个特性定义特征重要性分数。然后,将特征重要性分数应用于支持向量数据描述的权衡参数中,构建特征重要性正则化的支持向量数据描述(Feature Importance Regularized Support Vector Data Description, FIR-SVDD)。最后,在核空间中利用投影球面距离度量进行故障量化评估。采用田纳西-伊斯曼化工数据和HYDAC液压系统数据进行对比实验,结果表明所提方法具有更好的性能。
文摘【目的】全球离散格网系统(Discrete Global Grid Systems,DGGS)本质上是多尺度栅格结构,地理空间矢量与格网的集成是难点,矢量线格网化是其中的基本问题。现有方案多以平面格网单元中心(格心)连线为矢量线建模结果,但扩展到球面后建模精度降低,本文针对这一缺陷提出矢量线全球离散格网系统高精度建模方法。【方法】首先选择与地球拟合程度更高的菱形三十面体构建六边形格网系统,以3个相邻菱形面构成组合结构并建立三轴整数坐标系描述单元空间位置;然后根据矢量线首尾端点所在单元确定最优方向编码以减少搜索范围,通过编码邻近运算搜索矢量线经过的球面单元,以球面格心连线为建模结果并提出跨面矢量线处理方法;最后增加单元顶点(格点)作为结构要素,实现多结构要素矢量线建模,进一步提高建模精度。【结果】实验结果表明:本文方案能正确实现全球各个大洲海岸线格网化建模,确保格网化单元与矢量线拓扑相交,且相较平面格网建模结果兼具精度和效率优势。【结论】针对传统矢量数据格网建模方法的几何精度损失和拓扑畸变问题,本文提出高精度球面格网化建模方法,为矢量数据转换至格网同构处理提供有力支撑。
