如何评价炉石传说德鲁伊卡组 魔块城墙德

炉石传说 德鲁伊

完美女神 完美女神
回答
  • 崃克保B?  安好 崃克保B? 安好

    第一作者
    [1]魏玲,师义民.巴斯卡分布参数的bayes估计.纯粹数学与应用数学,1999,15(2):13-16.
    [2]魏玲,师义民.对数正态分布无失效数据的可靠性分析.西北大学学报(自然科学版),2000,30(1):1-3.
    [3]wei ling,qi jian-jun,shi yi-min.the eb estimation of scale-parameter for the two-parameter exponential d**tribution under the type-ⅱ censoring life test.mathematica applicata,2001,14(4):66-70.
    [4]ling wei,jian-jun qi,wen-xiu zhang.knowledge d**covery of dec**ion table based on support vector machine.in:proceedings of 2003 international conference on machine learning and cybernetics.ieee,2003,1195-1200.
    [5]魏玲,**军,张文修.基于支持向量机的决策系统知识发现.西安交通大学学报,2003,37(10):995-998.
    [6]魏玲,张文修.基于支持向量机集成的分类.计算机工程,2004,30(13):1-2,17.
    [7]魏玲,师义民.linex损失下一类分布族参数渐近最优的eb检验.西北大学学报(自然科学版),2004,34(5):517-521.
    [8]ling wei,wen-xiu zhang.attribute reduction based on equivalence relation defined on attribute set and its power set.in:b.dunin-keplicz,a.jankowski,a.skowron,and m.szczuka(eds.).international workshop on monitoring,security and rescue techniques in multiagent systems msras 2004,advances in soft computing.berlin heidelberg:springer-verlag,2005,317-326.
    [9]ling wei,wen-xiu zhang.a novel stat**tical method on dec**ion table analys**.lecture notes in computer science(ai 2004),2004,3339:973-978.
    [10]魏玲,张文修.决策表分析的统计依据.计算机科学,2005,32(4):19-21.
    [11]魏玲,**军,张文修.概念格与粗糙集的关系研究.计算机科学,2006,33(3):18-21.
    [12]魏玲.概念格属性约简理论与方法./张文修,姚一豫,梁怡.粗糙集与概念格.西安:西安交通大学出版社,2006:357-380.
    [13]魏玲,张文修.粗糙集约简的闭算子方法.计算机科学,2007,34(1):159-162,182.
    [14]ling wei,hong-ru li,wen-xiu zhang.knowledge reduction based on the equivalence relations defined on attribute set and its power set.**rmation sciences,2007,177(15):3178-3185.
    [15]魏玲,**军,张文修.决策形式背景的概念格属性约简.**科学e辑:信息科学,2008,38(2):195-208.wei ling,qi jianjun,zhang wenxiu.attribute reduction theory of concept lattice based on dec**ion formal contexts.science in china series f:**rmation science,2008,51(7):910-923.
    [16]ling wei,jian-jun qi.combination and decomposition theories of formal contexts based on same attribute set.lecture notes in computer science(rskt 2008),2008,5009:452-459.
    [17]ling wei,guang yao,wei zhao.object oriented concept lattice construction through the combination of formal contexts.in:proceedings of 2009 international conference on machine learning and cybernetics.ieee,2009,2127-2131.
    [18]ling wei,xiao-hua zhang,jian-jun qi.granular reduction of property-oriented concept lattices.lecture notes in computer science(iccs 2010),2010,6208:154-164.
    [19]ling wei,sheng-nan wang,wei zhao.methods to construct several kinds of concept lattices.in:proceedings of 2010 international conference on machine learning and cybernetics.ieee,2010,91-96.
    [20]ling wei,hui-yan hong,wei zhao.the relationship between property-oriented concept lattice and partition.in:proceedings of 2010 international conference on machine learning and cybernetics.ieee,2010,122-127.
    [21]ling wei,jian-jun qi.relation between concept lattice reduction and rough set reduction.knowledge-based systems,2010,23(8):934-938.
    [22]ling wei,jing zhang,hong-ying zhang.compar**on of concept lattice reduction based on d**cernbility matrixes.in:proceedings of 2011 international conference on machine learning and cybernetics.ieee,2011,1118-1123.
    [23]ling wei,qiang li.covering-based reduction of object-oriented concept lattices.lecture notes in computer science(rskt 2011),2011,**54:728-733.
    通讯作者
    [1]min-qian liu,ling wei,wei zhao.the reduction theory of object oriented concept lattices and property oriented concept lattices.lecture notes in computer science(rskt 2009),2009,5589:587-593.
    [2]shengnan wang,ling wei,qiang li.construct new lattices based on rough set theory.in:proceedings of 2010 2nd international conference on **rmation science and engineering,ieee,2010,5013-5016.
    [3]kesheng wu,ling wei.attribute reduction based on interval-valued formal contexts.in:proceedings of 2010 2nd international conference on **rmation science and engineering,ieee,2010,4978-4981.
    [4]赵玉锋,魏玲,刘敏茜.多背景横向合并属性特征分析.西北大学学报(自然科学版),2009,39(2):181-185.
    [5]赵玉锋,魏玲,王磊.模糊形式背景横向合并概念的生成.计算机科学,2009,36(8a):116-120.
    [6 姚广,魏玲,王磊.合成背景的面向属性概念格生成.西北大学学报(自然科学版),2010,40(1):1-4.
    [7]王磊,魏玲,姚广.横向合成背景的概念生成.西北大学学报(自然科学版),2010,40(2):195-198.
    [8]王彬弟,魏玲.基于关联格的概念格约简理论.山东大学学报(理学版),2010,45(9):20-26.
    [11]孙昱薇,魏玲,仇代远.基于基概念的面向属性概念格建格方法.西北大学学报(自然科学版),2011,41(1):11-14,18.
    第二作者
    [1]师义民,魏玲,肖华勇.冷贮备串联系统可靠性指标的估计.西北工业大学学报,2001,19(1):76-79.
    [2]赵炜,魏玲,许军,张毅.线性加权评价与聚类分析理论及应用.纯粹数学与应用数学,2002,18(2):121-125.
    [3]张文修,魏玲,徐萍.广义信息系统上的rough集理论.模糊系统与数学,2004,18(9):29-33.
    [4]张文修,魏玲,**军.概念格的属性约简理论与方法.**科学e辑:信息科学,2005,35(6):628-639.zhang wenxiu,wei ling,qi jianjun.attribute reduction theory and approach to concept lattice.science in china series f-**rmation science,2005,48(6):713-726.
    [5]jian-jun qi,ling wei,zeng-zhi li.a partitional view of concept lattice.lecture notes in computer science(rsfdgrc 2005),2005,3641:74-83.
    [6]wen-xiu zhang,ling wei,jian-jun qi.attribute reduction in concept lattice based on d**cernibility matrix.lecture notes in computer science(rsfdgrc 2005),2005,3642:157-165.
    [7]jian-jun qi,ling wei,zeng-zhi li.a computational model of trust.computer science and telecommunications,2005,7(3):16-20.
    [8]张文修,魏玲,**军,仇国芳.概念格约简泛化与概念粒逼近./苗夺谦,王国胤,刘清,林早阳,姚一豫.粒计算:过去、将来与展望.北京:科学出版社,2007:243-274.
    [9]jian-jun qi,ling wei.attribute reduction in cons**tent dec**ion formal context.**rmation technology journal,2008,7(1):170-174.
    [10]jian-jun qi,ling wei,yun-bo bai.composition of concept lattices.in:proceedings of 2008 international conference on machine learning and cybernetics.ieee,2008,2274-2279.
    [11]jian-jun qi,ling wei,yan-ping chen.correlation analys** between objects and attributes.lecture notes in computer science(rskt 2009),2009,5589:594-600.
    [12]qi jian-jun,wei ling,liu wei.concept lattice construction through the composition and decomposition of formal context.in:proceedings of 2010 international workshop on rough sets theory,2010,488-493.
    [13]jian-jun qi,ling wei,hui-yan hong.concept lattice construction about many-valued contexts.in:proceedings of 2011 international conference on machine learning and cybernetics.ieee,2011,1124-1129.

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