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基于直觉模糊集的时域证据组合方法研究 总被引:2,自引:0,他引:2
证据理论已广泛应用于时空信息融合领域,由于时域信息融合表现出明显的序贯性和动态性,为实现基于证据理论的时域信息融合,有效处理时域冲突信息,结合证据可靠性评估和证据折扣的思想,在直觉模糊框架内提出了一种基于复合可靠度的时域证据组合方法.首先定义一种基于可靠度的直觉模糊数排序方法,在此基础上提出一种基于直觉模糊多属性决策的证据可靠性评估方法;然后,基于此方法对时域信息序列中相邻时间节点的证据可靠性进行评估,得到时域证据的相对可靠性因子;最后,结合由时域证据可靠度衰减模型得到的实时可靠性因子,得到时域证据的复合可靠性因子,再基于证据折扣运算和Dempster证据组合规则提出一种基于复合可靠度的时域证据组合方法.数值算例和仿真表明,该方法具有较强的时间敏感性,充分体现了时域信息融合的动态性特点,可以较好地处理时域证据中的冲突信息,基于该方法构建的融合识别系统具有较强的抗干扰能力. 相似文献
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在信息融合系统中,各传感器提供的信息不一定完全可靠,在融合前有必要对传感器的可靠性进行评估,进而对其提供的信息进行预处理。基于证据理论,在传感器混淆矩阵的基础上定义了后验概率向量,通过分析后验概率向量与传感器输出证据之间的关系对传感器可靠性进行评估;然后利用传感器的可靠性因子对证据进行折扣运算,实现对信息的预处理;最后利用Dempster组合规则进行融合。基于证据理论的融合识别算例表明,所提出的方法综合利用了传感器的先验信息和动态输出,可以较好地反映传感器的性能,并能够有效降低可靠性传感器的影响,具有较好的融合效果。 相似文献
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基于模糊集的证据组合方法及其应用 总被引:1,自引:1,他引:0
为解决高度冲突证据的合成问题,提出一种基于模糊集的证据组合方法.对证据集中的所有证据对的冲突权进行计算,构造了冲突权矩阵,并提出了一种根据冲突权大小甄别冲突源的方法.引入模糊集理论,根据证据所引起的冲突权大小定义了证据的模糊可信度.按模糊可信度对证据进行预处理,然后用Dempster法则进行组合.实例表明,该方法能有效处理冲突证据的合成问题,保证了冲突证据合成的合理性和可靠性. 相似文献
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证据理论是常用的一种决策级信息融合方法,能有效处理不确定性信息.然而该方法在融合冲突证据时却可能会得到与常理相悖的结论.针对这一问题,对已有解决方法进行了总结,在此基础上提出一种新的折扣方法,综合考虑了证据之间的相互冲突情况和各证据自身的区分能力.鉴于冲突、区分能力等概念的定义具有模糊性,引入模糊集合予以表示,定义了它们的模糊隶属函数,并设计了相应的模糊推理规则以获取折扣值.算例表明,新方法对一致性证据影响甚微,而对冲突证据能够进行有效处理,得到合理的融合结果. 相似文献
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在基于证据理论的信息融合故障诊断方法中,诊断证据的可靠性高低将会直接影响诊断结果的准确性.而现有的大多数方法并没有全面地评估证据的可靠性,从而常常导致融合诊断结果的不准确.决定证据可靠性的因素主要有传感器的精度与证据获取方法的性能,以及传感器运行环境中的不确定性因素,可将它们分别理解为静态和动态因素.本文利用基于Pignisti。的指标函数优化算法获得静态折扣因子,用其对原证据进行修正;接着提出基于Pignistic向量的证据相似度度量方法获取动态折扣因子,用其对证据进行再次修正,并利用Dempster组合规则融合经两次修正后的证据,得到诊断结果.最后,通过在多功能柔性转子试验台上的实验,验证了所提方法的有效性. 相似文献
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针对时域不确定信息的融合难题,为充分体现时域信息融合的动态性特点和时间因素对融合的影响,在证据理论的基础上,提出一种考虑决策者时序偏好的时域证据融合方法。首先将决策者对时序的偏好融入时域证据融合,通过分析时域证据序列的特点,在定义时序记忆因子的基础上,对决策者的时序偏好进行度量;然后通过构建优化模型求解时序权重,再结合证据信任度的概念,对证据源进行修正;最后利用Dempster组合规则对修正后的证据进行融合。数值算例表明,与没有考虑时间因素的融合方法相比,考虑决策者时序偏好的证据融合方法可以有效处理时域信息序列中的冲突信息,得到合理的融合结果;同时,所提方法充分考虑了时域证据序列的信任度和决策者的主观偏好,可以反映决策者主观因素对时域证据融合的影响,较好地体现了时域证据融合的动态性特点。 相似文献
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Dempster-Shafer证据理论广泛应用于信息融合中, 但是在证据高冲突情况下基于经典D-S证据组合规则的融合结果存在反直观的问题。针对这一问题, 提出一种基于平均偏离度的证据组合方法。首先引入证据距离函数获得各证据体的相互支持度, 并将支持度归一化为证据的信任度。对所有的证据进行信任度加权平均, 获得一个参考证据。然后利用该参考证据对各个原始证据进行偏离度的判定及修正。最后利用Dempster-Shafer规则完成证据的组合。实验结果表明, 新方法提高了融合结果的可靠性和合理性, 可以有效地处理高冲突证据。 相似文献
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兼具可靠性和重要性的证据融合问题目前仅局限于折扣处理阶段, 尚未深入到融合规则的构建之中. 为解决此问题, 首先结合现有成果的解决思路分析其中存在的问题; 然后构建能够对基本信度分配函数进行可靠性/重要性双重折扣处理且满足交换律的证据折扣方法, 在此基础上, 基于Dempster规则和Murphy规则从非补偿性与补偿性协调视角构建可以平衡可靠性和重要性的补偿协调融合规则; 最后通过数值对比分析验证所提出方法的科学性.
相似文献12.
软件可靠性增长模型中由于测试阶段和实际运行阶段环境的不同导致了失效强度函数的判断偏差。在Musa执行时间模型中的经典模型M-O对数泊松执行时间模型基础上,提出考虑环境因素的对数泊松模型,该模型能较好的刻画失效强度函数变化规律,并给出参数估计公式。通过对失效数据集的实验,结果表明该模型具有较好的拟合效果。 相似文献
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Recently, researches on smart phones have received attentions because the wide potential applications. One of interesting and useful topic is mining and predicting the users’ mobile application (App) usage behaviors. With more and more Apps installed in users’ smart phone, the users may spend much time to find the Apps they want to use by swiping the screen. App prediction systems benefit for reducing search time and launching time since the Apps which may be launched can preload in the memory before they are actually used. Although some previous studies had been proposed on the problem of App usage analysis, they recommend Apps for users only based on the frequencies of App usages. We consider that the relationship between App usage demands and users’ recent spatial and temporal behaviors may be strong. In this paper, we propose Spatial and Temporal App Recommender (STAR), a novel framework to predict and recommend the Apps for mobile users under a smart phone environment. The STAR framework consists of four major modules. We first find the meaningful and semantic location movements from the geographic GPS trajectory data by the Spatial Relation Mining Module and generate the suitable temporal segments by the Temporal Relation Mining Module. Then, we design Spatial and Temporal App Usage Pattern Mine (STAUP-Mine) algorithm to efficiently discover mobile users’ Spatial and Temporal App Usage Patterns (STAUPs). Furthermore, an App Usage Demand Prediction Module is presented to predict the following App usage demands according to the discovered STAUPs and spatial/temporal relations. To our knowledge, this is the first study to simultaneously consider the spatial movements, temporal properties and App usage behavior for mining App usage pattern and demand prediction. Through rigorous experimental analysis from two real mobile App datasets, STAR framework delivers an excellent prediction performance. 相似文献
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In aspect-oriented programming (AOP) a cross-cutting concern is implemented in an aspect. An aspect weaver blends code from the aspect into a program’s code at programmer-specified cut points, yielding an aspect-enhanced program. In this paper, we apply some of the concepts from the AOP paradigm to data. Like code, data also has cross-cutting concerns such as versioning, security, privacy, and reliability. We propose modeling a cross-cutting data concern as a schema aspect. A schema aspect describes the structure of the metadata in the cross-cutting concern, identifies the types of data elements that can be wrapped with metadata, i.e., the cut points, and provides some simple constraints on the use of the metadata. Several schema aspects can be applied to a single data collection, though in this paper we focus on just two aspects: a reliability aspect and a temporal aspect. We show how to weave the schema for these two aspects together with the schema for the data into a single, unified schema that we call a schema tapestry. The tapestry guides the construction, interpretation, and validation of an aspect-enhanced data collection. 相似文献
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提出了一种基于D-S证据理论的Bayes可靠性评估方案,很好地表达和利用了Bayes方法中的"不确定的"先验信息。在无替换定数截尾试验样本下,研究了指数寿命型产品的可靠性指标的估计问题,提出了可靠性评估的两种方法 :通过融合可靠性指标的后验分布进行综合评估和通过融合可靠性指标的后验置信区间进行综合评估。数值实例表明,利用所提出的方法得到的评估结果是"谨慎的"和合理的。 相似文献
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《Data & Knowledge Engineering》2008,64(3):752-773
In aspect-oriented programming (AOP) a cross-cutting concern is implemented in an aspect. An aspect weaver blends code from the aspect into a program’s code at programmer-specified cut points, yielding an aspect-enhanced program. In this paper, we apply some of the concepts from the AOP paradigm to data. Like code, data also has cross-cutting concerns such as versioning, security, privacy, and reliability. We propose modeling a cross-cutting data concern as a schema aspect. A schema aspect describes the structure of the metadata in the cross-cutting concern, identifies the types of data elements that can be wrapped with metadata, i.e., the cut points, and provides some simple constraints on the use of the metadata. Several schema aspects can be applied to a single data collection, though in this paper we focus on just two aspects: a reliability aspect and a temporal aspect. We show how to weave the schema for these two aspects together with the schema for the data into a single, unified schema that we call a schema tapestry. The tapestry guides the construction, interpretation, and validation of an aspect-enhanced data collection. 相似文献
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Data fusion in time domain is sequential and dynamic. Methods to deal with evidence conflict in spatial domain may not suitable in temporal domain. It is significant to determine the dynamic credibility of evidence in time domain. The Markovian requirement of time domain fusion is analyzed based on Dempster's combination rule and evidence discount theory. And the credibility decay model is presented to get the dynamic evidence credibility. Then the evidence is discounted by dynamic discount factor. It's illustrated that such model can satisfied the requirement of data fusion in time domain. Proper and solid decision can be made by this approach. 相似文献
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为了有效融合高度冲突的证据,以Murphy方法和邓勇加权平均法为基础,提出了一种新的基于加权证据距离的证据组合方法。用Murphy方法确定各证据体的权重,采用修正的City Block距离加权平均求证据间的两两距离,进而获取各证据被其他所有证据支持的程度,归一化各证据的总支持度作为该证据的权重,对多源证据加权平均后再利用Dempster组合规则实现信息融合。实验结果表明,该方法能够更加有效快速地识别出目标,拥有更快的收敛速度。 相似文献