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Function S-Rough sets and its applications 被引量:25
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作者 Cui Yuquan Shi Kaiquan 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2006年第2期331-338,共8页
Based on S-rough sets(singular rough sets), this paper presents function S-rough sets (function singular rough sets)and its mathematical structures and features. Function S-rough sets has two forms: function one ... Based on S-rough sets(singular rough sets), this paper presents function S-rough sets (function singular rough sets)and its mathematical structures and features. Function S-rough sets has two forms: function one direction S-rough sets (function one direction singular rough sets) and function two direction S-rough sets (function two direction singular rough sets). This paper advances the relationship theorem of function S-rough sets and S-rough sets. Function S-rough sets is the general form of S-rough sets, and S-rough sets is the special ease of function S-rough sets. In this paper, applications of function S-rough sets in rough law mining-discovery of system are given. Function S-rough sets is a new research direction of rough sets and rough system. 展开更多
关键词 function S-rough sets structure of function S-rough sets relationship theorem rough law mining-discovery applications.
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Function S-rough sets and mining-discovery of rough law in systems 被引量:25
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作者 Shi Kaiquan Xia Jiarong 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2006年第4期919-926,共8页
Function S-rough sets (function singular rough sets) is defined on a -function equivalence class [u]. Function S-rough sets is the extension form of S-rough sets. By using the function S-rough sets, this paper gives... Function S-rough sets (function singular rough sets) is defined on a -function equivalence class [u]. Function S-rough sets is the extension form of S-rough sets. By using the function S-rough sets, this paper gives rough law generation model of a-function equivalence class, discussion on law mining and law discovery in systems, and application of law mining and law discovery in communication system. Function S-rough sets is a new theory and method in law mining research. 展开更多
关键词 function S-rough sets structure of function S-rough sets relationship theorem rough law mining-discovery applications.
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FIXED POINTS OF NONEXPANSIVE MAPPINGS ON STAR-SHAPED SUBSETS OF A CONVEX METRIC SPACE
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作者 邓磊 丁协平 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI 1992年第2期135-141,共7页
In this paper, we give some characteristic properties of star-shaped sets which include a subset of a convex metric space. Using the characteristic properties, we discuss the existence problems of fixed points of none... In this paper, we give some characteristic properties of star-shaped sets which include a subset of a convex metric space. Using the characteristic properties, we discuss the existence problems of fixed points of nonexpansive type mappings on star-shaped subsets of convex metric spaces, which generalize the recent results obtained by Ding Xie-ping, Beg and Azam. Finally, we give an example which shows that our generalizations are essential. 展开更多
关键词 star-shaped set star centre normal structure of a star-shaped set
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Contour tracking using weighted structure tensor based variational level set
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作者 胡宏伟 马波 曹淑娟 《Journal of Beijing Institute of Technology》 EI CAS 2014年第2期218-225,共8页
A novel contour tracking method using weighted structure tensor based variational level set is proposed in this paper.The image is first converted to weighted structure tensor field by extracting apositive definite sy... A novel contour tracking method using weighted structure tensor based variational level set is proposed in this paper.The image is first converted to weighted structure tensor field by extracting apositive definite symmetric covariance matrix for each pixel.Then,a level set method is employed to represent object contour implicitly which separates the image domain into two areas each modeled by tensor field based Gaussian mixture model separately.By solving agradient flow equation of energy functional with respect to the level set,the object contour will converge to its real profile in the newly arrived frame.Experimental results on several video sequences demonstrate the better performance of our method than the other two contour tracking algorithms. 展开更多
关键词 contour tracking weighted structure tensor Gaussian mixture model level set
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Characteristics of Dengying Fm sedimentary sequence in the central-western Sichuan Basin and their controlling effect on gas accumulation 被引量:1
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作者 Wen Long Yang Yueming +5 位作者 You Chuanqiang Zhang Xihua Peng Hanlin Wang Wenzhi Luo Bing Luo Wenjun 《Natural Gas Industry B》 2016年第5期428-438,共11页
A large gas reservoir in the Sinian Dengying Fm was recently discovered in Anyue area,central Sichuan Basin.In order to promote the oil and gas exploration in this area,it is of great significance to sustainably deepe... A large gas reservoir in the Sinian Dengying Fm was recently discovered in Anyue area,central Sichuan Basin.In order to promote the oil and gas exploration in this area,it is of great significance to sustainably deepen the analysis on its high-quality reservoir distribution and sourcereservoir assemblage.In this paper,a series of studies were performed on the sequence frameworks and sedimentary filling evolution characteristics of the Dengying Fm in centralewestern Sichuan Basin,and their controlling effects on the reservoir development and distribution and source-reservoir assemblage during its sedimentation.It is shown that the Deyang-Anyue paleo-rift is,on the whole,distributed in a NW direction,and is morphologically wide and steep in the north,but narrow and gentle in the south.There are two rift boundaries of the second and fourth members of Dengying Fm(Deng 2 Member and Deng 4 Member,respectively).The rift of Deng 2 Member is distributed in the shape of“U”in Deyang-Neijiang area.Dengying Fm is divided into four third-order sequences(SQ1-SQ4).In SQ3 of Gaoshiti-Moxi area,central Sichuan Basin,a complete sedimentation reflection structure of transgressive overlap and regressive progradation can be identified with earlyemiddle Deng 4 Member platform margin.The paleo-rift was in embryo before the sedimentation of Sinian,so the sedimentary filling and lithofacies distribution of the Sinian were influenced by the inherited activities of pre-Sinian rifts.The favorable distribution zones of highquality reservoirs are located at the rift margins of Deng 2 and Deng 4 Members that were formed respectively during the SQ2 and SQ4 and the platform margin of early Deng 4 Member that was formed during the SQ3.A laterally connected source-reservoir assemblage occurs at the margins of Deng 2 and Deng 4 Members around the Lower Cambrian source rocks of the paleo-rift.The northwestward extending margin zone along the eastern flank of the paleo-rift shows a good potential for hydrocarbon accumulation. 展开更多
关键词 Sichuan basin SINIAN Gas accumulation Sedimentary structure setting Stratigraphic sequence Sedimentary filling RESERVOIRS Source-reservoir assemblage Controlling factors
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Deep Learning-Based Prediction of Seepage Flow in Soil-Like Porous Media
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作者 Zhenzhen Shen Kang Yang +6 位作者 Dengfeng Wei Quansheng Liang Zhenpeng Ma Hong Wang Keyu Wang Chunwei Zhang Xiaohu Yang 《Fluid Dynamics & Materials Processing》 2025年第11期2741-2760,共20页
The rapid prediction of seepage mass flow in soil is essential for understanding fluid transport in porous media.This study proposes a new method for fast prediction of soil seepage mass flow by combining mesoscopic m... The rapid prediction of seepage mass flow in soil is essential for understanding fluid transport in porous media.This study proposes a new method for fast prediction of soil seepage mass flow by combining mesoscopic modeling with deep learning.Porous media structures were generated using the Quartet Structure Generation Set(QSGS)method,and a mesoscopic-scale seepage calculation model was applied to compute flow rates.These results were then used to train a deep learning model for rapid prediction.The analysis shows that larger average pore diameters lead to higher internal flow velocities and mass flow rates,while pressure drops significantly at the throats of fine pores.The trained model predicts seepage mass flow rates with deviations within±20%,achieving a root mean square error of 0.24261 and an average deviation of-0.02197.Importantly,the method performs well even with limited training data,though image-based deep learning approaches may yield better accuracy when larger datasets are available. 展开更多
关键词 Seepage flow lattice Boltzmann method(LBM) multilayer perceptron(MLP) quartet structure generation set(QSGS)
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Parameter Ecology for Feedback Vertex Set
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作者 Bart M.P.Jansen Venkatesh Raman Martin Vatshelle 《Tsinghua Science and Technology》 SCIE EI CAS 2014年第4期387-409,共23页
This paper deals with the FEEDBACK VERTEX SET problem on undirected graphs, which asks for the existence of a vertex set of bounded size that intersects all cycles. Due it is theoretical and practical importance,the p... This paper deals with the FEEDBACK VERTEX SET problem on undirected graphs, which asks for the existence of a vertex set of bounded size that intersects all cycles. Due it is theoretical and practical importance,the problem has been the subject of intensive study. Motivated by the parameter ecology program we attempt to classify the parameterized and kernelization complexity of FEEDBACK VERTEX SET for a wide range of parameters.We survey known results and present several new complexity classifications. For example, we prove that FEEDBACK VERTEX SET is fixed-parameter tractable parameterized by the vertex-deletion distance to a chordal graph. We also prove that the problem admits a polynomial kernel when parameterized by the vertex-deletion distance to a pseudo forest, a graph in which every connected component has at most one cycle. In contrast, we prove that a slightly smaller parameterization does not allow for a polynomial kernel unless NP coNP=poly and the polynomial-time hierarchy collapses. 展开更多
关键词 feedback vertex set parameterized complexity parameter ecology program structural parameterizations kernelization
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