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基于粗糙集的模糊决策算法 总被引:8,自引:0,他引:8
给出一种从连续决策表中提取模糊决策规则的规则提取算法。首先,转化连续属性值为模糊值;然后,给出两个不同对象的模糊属性值关于相应连续属性的相似度;其次,给出了λ相似关系与λ相似类的定义。根据λ相似关系,给出粗糙-模糊空间中的下近似与上近似概念;最后,结合模糊集与粗糙集理论的思想,给出一种从连续值域决策表获取决策规则的算法,并通过实例说明该算法的有效性。 相似文献
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M2对宏观经济的时滞效应及时变弹性分析 总被引:1,自引:0,他引:1
金融危机背景下我国出台的一系列货币政策导致M2快速增长,但其对我国实体经济的影响效应时滞及弹性效果分析目前尚无定论。本文建立了VARX模型来测算M2的增加对宏观经济的影响效应;结果表明,M2的增加对经济增长的拉动作用在滞后第2季度达到最大,但对通货膨胀的冲击效应相对较小时滞更长,在第5~6个季度才能达到最大。另外,为了分析宏观经济指标对M2的弹性系数在不同历史时期的变化,建立了时变Bayesian弹性分析模型测算M2对宏观经济影响效应的变动状况;结果表明:GDP、CPI对M2的弹性系数具有时变性,而M2拉动经济增长的作用效果自1998年以来呈逐年下降趋势。 相似文献
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我国经济增长与产业结构演进关系的研究——基于面板数据模型的实证分析 总被引:6,自引:0,他引:6
本文运用面板数据模型,对我国各省1996-2005年人均GDP及三次产业产值比重的关系分别进行了模型拟合,结论认为:我国经济增长对产业结构变化的影响显著,而后者对前者的影响在统计上并不显著,我国经济增长模式是需求导向型的。其次,就各次产业与人均GDP的关系看,第一产业与人均GDP呈现负相关关系,而第二、三产业与人均GDP呈现正相关关系。 相似文献
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文章基于Bayes空间计量视角,分析我国GDP增长与投资、消费、出口等因素之间的关系模式,并将区域集聚效应引入模型.研究结果表明:中国经济增长存在空间相关性,表现为外生冲击引起的空间误差自相关,将空间相关和空间异质性因素同时纳入模型后的分析结果显示:消费增长对GDP增长的拉动作用占主导地位,超过投资和出口影响的总和,这与普通回归模型分析结果有着显著的差异;同时,GDP增长的空间计量模型显现出区域集聚效应差异:西部地区的增长显著低于其它区域,东部和中部地区之间差异并不显著. 相似文献
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郑丽琴 《数学的实践与认识》2014,(4)
以高等教育为主体的人力资本投入对地区经济增长具有推动力已成为经济发展在理论和实践上的普遍认识.首次将LMDI分解法引入高等教育经费投入与GDP增长之间的动态关系实证研究,通过构建GDP总量分解模型,深入分析二者之间内在的因果驱动关系.分析结果表明,对我国而言,代表高等教育经济投入总量的活动效应对GDP变动贡献最大,是主要驱动力;代表教育经费在区域问分布的结构效应对GDP变动影响很小;代表单位教育经费驱动效率的效率效应对GDP增长起到了重要促进作用. 相似文献
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新常态下,我国对外开放增速放缓,一定程度上影响了我国区域经济发展和产业转型.因此选取2005年-2015年的季度数据,通过全球向量自回归模型(GVAR)实证分析对外开放对区域经济增长和产业转型的动态影响.研究结果显示:1)外资引进的增加对区域经济增长有显著的拉动作用,而对产业高级化的作用有明显的区域特征,除南部沿海经济区和大西北经济区受到抑制外,其他的都呈现带动效果.2)对外贸易对区域经济增长和产业高级化都呈现出了阻碍作用. 相似文献
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运用时间序列模型的动态计量方法对科研投入的效果进行分析.以GDP作为检验科研投入效果的经济指标,对1980-2001年我国科研投入对经济增长的贡献作用进行实证分析,构建了科研投入与GDP的自回归分布滞后(ADL)模型,以此为起点并结合平稳性检验和协整检验建立了动态计量经济学模型的一般形式即误差修正模型(ECM),该模型刻画了科研投入与经济增长二者之间长期稳定的均衡关系. 相似文献
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犹豫模糊集的截集及其性质 总被引:1,自引:0,他引:1
谢海 《数学的实践与认识》2017,(3):251-258
通过引入犹豫模糊集的截集概念并研究截集的性质,建立了沟通犹豫模糊集合与经典集合之间的桥梁.进一步,讨论了犹豫模糊关系的截关系及其性质. 相似文献
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An adjustable approach to fuzzy soft set based decision making 总被引:2,自引:0,他引:2
Molodtsov’s soft set theory was originally proposed as a general mathematical tool for dealing with uncertainty. Recently, decision making based on (fuzzy) soft sets has found paramount importance. This paper aims to give deeper insights into decision making based on fuzzy soft sets. We discuss the validity of the Roy-Maji method and show its true limitations. We point out that the choice value designed for the crisp case is no longer fit to solve decision making problems involving fuzzy soft sets. By means of level soft sets, we present an adjustable approach to fuzzy soft set based decision making and give some illustrative examples. Moreover, the weighted fuzzy soft set is introduced and its application to decision making is also investigated. 相似文献
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A fuzzy rule-based system for handwritten Chinese characters recognition based on radical extraction 总被引:1,自引:0,他引:1
In this paper, a fuzzy rule-based system for handwritten Chinese characters recognition (HCCR) based on radical extraction is proposed. Since the writings of handwritten Chinese characters vary a lot, we adopt fuzzy set theory to deal with the recognition of these fuzzy patterns. Candidates of strokes are provided with confidence values to obtain more reliable and accurate results. Furthermore, hierarchical fuzzy rule sets that represent the character structures are used to combine the extracted strokes into compound strokes or radicals. The flexible expansion ability thus provided is very promising. Also, since the number of rules in a fuzzy system is much less than that in a general rule-based system, the computation effort is not difficult. An average of 99.63% recognition rate of 542 test categories that are selected from the 100th sample set of HCCRBASE (character image database provided by CCL, ITRI, Taiwan) is obtained. The experimental results not only verify the feasibility of the proposed system, but also suggest that applying fuzzy set theory to HCCR is an efficient and promising approach. 相似文献
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针对基于Vague集信息的多属性群决策专家水平评判问题提出了两种评判方法.首先引进了基于Vague集信息的多属性群决策信息体(即决策信息体)的相关概念,通过决策信息体构造了基于Vague集信息的一致性决策矩阵及模糊熵,其次利用Vague集信息的相似度量以及Vague集信息的模糊熵两种信息不确定性度量方法,对基于Vague集信息的多属性群决策专家水平评判问题提出了两种评判方法,即统计分析方法和模糊熵分析方法,对专家的评判水平进行排序.最后,通过一个算例说明两种方法的一致性、有效性和实用性. 相似文献
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Interpretability is one of the key concepts in many of the applications using the fuzzy rule-based approach. It is well known that there are many different criteria around this concept, the complexity being one of them. In this paper, we focus our efforts in reducing the complexity of the fuzzy rule sets. One of the most interesting approaches for learning fuzzy rules is the iterative rule learning approach. It is mainly characterized by obtaining rules covering few examples in final stages, being in most cases useless to represent the knowledge. This behavior is due to the specificity of the extracted rules, which eventually creates more complex set of rules. Thus, we propose a modified version of the iterative rule learning algorithm in order to extract simple rules relaxing this natural trend. The main idea is to change the rule extraction process to be able to obtain more general rules, using pruned searching spaces together with a knowledge simplification scheme able to replace learned rules. The experimental results prove that this purpose is achieved. The new proposal reduces the complexity at both, the rule and rule base levels, maintaining the accuracy regarding to previous versions of the algorithm. 相似文献
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Some similarity measures of intuitionistic fuzzy sets and their applications to multiple attribute decision making 总被引:1,自引:0,他引:1
Zeshui Xu 《Fuzzy Optimization and Decision Making》2007,6(2):109-121
Atanassov (1986) defined the notion of intuitionistic fuzzy set, which is a generalization of the notion of Zadeh’ fuzzy set.
In this paper, we first develop some similarity measures of intuitionistic fuzzy sets. Then, we define the notions of positive
ideal intuitionistic fuzzy set and negative ideal intuitionistic fuzzy set. Finally, we apply the similarity measures to multiple
attribute decision making under intuitionistic fuzzy environment. 相似文献
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首先通过相识集、招标集、投标集和任务集的概念 ,描述制造执行系统中的调度 Agent与资源 A-gent间任务招投标过程模型 ;基于任务的属性和资源 Agent完成任务的成本、质量、负荷和时间等属性 ,定义论域上的模糊集 ,将模糊集中的隶属度函数作为粗集的属性 ,在模糊集上作截集 ,从而获得系统的分类知识 ;收集样本数据 ,构造并分析决策表 ,进而获得调度 Agent调度决策知识 ;应用调度知识进行推理 ,从争取获得招标任务的若干个资源 Agent中 ,选出最适合招标任务的中标者 . 相似文献
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The k nearest neighbor rule (k-NNR) is a well-known nonparametric decision rule in pattern classification. Fuzzy set theory has been widely used to represent the uncertainty of class membership. Several researchers extended conventional k-NNR to fuzzy k-NNR, such as Bezdek et al. [Fuzzy Sets and Systems 18 (1986) 237–256], Keller et al. [IEEE Trans. Syst. Man, and Cybern. 15(4) (1985) 580–585], Béreau and Dubuisson [Fuzzy Sets and Systems 44 (1991) 17–32]. In this paper, we describe a fuzzy generalized k-NN algorithm. This algorithm is a unified approach to a variety of fuzzy k-NNR's. Then we create the strong consistency of posterior risk of the fuzzy generalized NNR. 相似文献