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《计算机工程与应用》2016,(22)
为了解决依据专家知识推断贝叶斯网络中条件概率表时存在的个体推断信息缺乏有效性以及整体集成结果缺乏科学性的问题,提出了有利于实现判断对象更直观、判断方式更简便的推断信息约简机理,然后将层次分析法中两两比较与判断矩阵分别作为主观条件概率信息的提取手段与信息载体,构建了能够从宏微观推断信息中提取最优条件概率的专家相对推断方法,该方法一方面可以克服传统方法中因专家推断能力有限的现实约束而造成个体推断信息容易缺乏有效性的问题,另一方面也能够对专家个体推断信息进行有效综合集成、保证决策结果的科学性。在此基础上遵循由前至后的推断顺序提出了贝叶斯网络的构建过程,最后应用数值对比分析和案例模拟分析验证了提出方法的科学有效性和应用可行性。 相似文献
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拓扑结构是重要的网络性能参数之一,尤其是对网络监控和管理而言,获取网络拓扑是一个很有意义的基础问题。网络编码技术的出现为网络拓扑推断提供了新的思路,中间节点的网络编码操作使得编码数据与网络拓扑结构之间存在着紧密的联系,基于网络编码的拓扑推断正是利用这种联系对网络拓扑结构进行分析识别。与利用网络层析成像实现拓扑推断相比,基于网络编码的拓扑推断有许多优势,如提高拓扑推断的准确性、降低推断算法的复杂度等。总结了网络编码技术在网络拓扑推断中的应用及研究现状。 相似文献
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为了提高自治域(autonomous systems,AS)关系推断的准确性,分析了现有的AS关系推断算法,指出其存在的不足,提出以IRR数据库为基础,由已知As关系推断未知AS关系的改进算法.首先从IRR数据库中提取AS关系,并以此为种子推断未知的AS关系,通过计算AS的度提取包含对等关系的三元组来推断对等关系,最后修正推断结果.实验结果表明,该算法能显著提高AS关系特别是对等关系的准确性. 相似文献
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基于网络层析成像技术的拓扑推断 总被引:5,自引:0,他引:5
网络层析成像是近年来新兴的一种网络测量技术,该技术结合了网络测量和统计推断,可以解决网络测量的部分难题.网络拓扑推断是网络层析成像技术的重要应用之一,基于网络层析成像技术的拓扑推断通过端到端的测量即可推断网络内部的拓扑结构,而不需要内部节点的合作.系统地总结了基于网络层析成像的拓扑推断技术的研究现状,对国内外研究进展进行了讨论,最后讨论了当前拓扑推断中存在的问题,并讨论了未来的研究方向. 相似文献
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文法推断属于形式语言的归纳学习问题,它研究如何从语言的有限信息出发,通过归纳推断得到语言的语法定义.文章综述文法推断研究的历史和现状.首先阐述文法推断的理论模型,接着罗列上下文无关文法类及其非平凡子类、隐马尔可夫模型以及随机上下文无关文法的推断方法,最后简介文法推断的应用,并展望其发展趋势. 相似文献
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针对依据专家知识推断贝叶斯网络中条件概率表(CPT)时存在的个体推断信息缺乏完备性和精确性以及整体集成结果缺乏科学性的问题,提出了基于证据理论/层次分析法(DS/AHP)的能够从专家推断信息中提取最优条件概率的方法.首先,通过引入DS/AHP方法中的知识矩阵提出了有利于实现判断对象更直观、判断方式更完善的推断信息提取机制;其次,在此基础上遵循由前至后的推断顺序提出了贝叶斯网络的构建过程;最后,应用传统方法与提出方法对同一贝叶斯网络中的缺失条件概率表进行了推断.数值对比分析表明,所提方法能够在提高计算效率的同时将累计总偏差降低41%,验证了所提方法的科学有效性和应用可行性. 相似文献
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《计算机科学与探索》2016,(12):1662-1672
用户以不同的角色在城市中不同的地域间从事各种活动,如何通过用户活动的地域推断他们的角色,以及通过用户的角色推断他们有可能频繁活动的地域结构,是用户移动性领域研究的挑战性问题。通过从用户所发微博中提取必需的情境要素,如用户ID、check-ins和GPS坐标等,对用户的移动规律建立用户角色与城市地域结构的互推断模型。实验结果表明,该模型无论在利用用户角色推断城市地域结构,还是在利用城市地域结构推断用户角色方面,均取得了较好的性能。 相似文献
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运用多项式方程方法,设计一种多率自校正GLQG推理控制器。通过采用推理控制系统I/O模型,把推理估计、LQG最优控制和自校正控制有机地结合起来,简化了推理控制系统的设计,实现了自校正控制,并可用于非最小相位系统和开环不稳定系统。 相似文献
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A definition for the reliability of inferential sensor predictions is provided. A data-driven Bayesian framework for real-time performance assessment of inferential sensors is proposed. The main focus is on characterizing the effect of operating space on the reliability of inferential sensor predictions. A holistic, quantitative measure of the reliability of the inferential sensor predictions is introduced. A methodology is provided to define objective prior probabilities over plausible classes of reliability based on the total misclassification cost. The real-time performance assessment of multi-model inferential sensors is also discussed. The application of the method does not depend on the identification techniques employed for model development. Furthermore, on-line implementation of the method is computationally efficient. The effectiveness of the method is demonstrated through simulation and industrial case studies. 相似文献
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An inferential semantics for full Higher Order Logic (HOL) is proposed. The paper presents a constructive notion of model, that being able to capture relevant computational aspects is particularly suited for the applications of HOL to computer science. The inferential semantics is based on the introduction of new abstract deduction structures (ADS) that express the action of the Comprehension Axiom in a Higher Order Logic proof. The ADS’s allow to define an inferential algebra of higher order potential proof-trees, endowed with two binary operations, the abstraction and the contraction, each consisting of constructive reductions between potential proofs. Typed formulas are interpreted by sequent trees, and the operations between trees correspond to the logical connectives of the interpreted formula. Higher order logic is sound and complete w.r.t. the given inferential semantics. 相似文献
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传统的审计方法解决了一般的推理审计问题,但是在审计的中间阶段没有考虑依赖关系中数据的可用性,从而会产生较多的冗余审计。该文针对多级安全数据库的推理审计问题提出了一种采用基于属性关联的方法,解决了基于FD的推理审计问题,并且解决了在审计中间阶段造成的数据冗余问题,通过进行优化提高了效率。 相似文献
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Two distinct types of inferential control strategies for the single-input/single-output (SISO) system of a packed-bed reactor are investigated, i.e. non-linear inferential control (NLIC)—the state feedback control (SFC) scheme—and linear inferential control (LIC)—the internal model control (IMC) scheme—to deal with non-linear and unmeasured output process control problems, and the effects of modelling errors and measurement noise on control system performance. The basic structure of an inferential control system is coupled with a state estimator and a controller consisting of the process model and a filter with adjustable parameter, A non-linear estimator is used to estimate the state variables of the process from the temperature measurements. Simulation results have shown that the performances of the SFC scheme are much better than those of the IMC scheme, in spite of modelling errors and measurement noise. The results also indicate that a substantial improvement in control is possible using NLIC. 相似文献
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In many industrial plants, development and implementation of advanced monitoring and control techniques require real-time measurement of process quality variables. However, on-line acquisition of such data may involve difficulties due to inadequacy of measurement techniques or low reliability of measuring devices. To overcome the shortcomings of traditional instrumentation, inferential sensors have been designed to infer process quality indicators from real-time measurable process variables. In recent years, due to the demonstrated advantages of Bayesian methods, interest in investigating the application of these methods for design of inferential sensors has grown. However, the potential of Bayesian methods for inferential modeling practices in the process industry has not yet been fully realized. This paper provides a general introduction to the main steps involved in development and implementation of industrial inferential sensors, and presents an overview of the relevant Bayesian methods for inferential modeling. 相似文献
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K. Warne G. Prasad S. Rezvani L. Maguire 《Engineering Applications of Artificial Intelligence》2004,17(8):871-885
In industry today many products are sold for their efficacy rather than their chemical composition. Many variables (dependent variables), which characterize the quality of the final product in a manufacturing process, can be difficult to measure in real-time. Measurement difficulties can be due to a variety of reasons, including: (1) Reliability of on-line sensors, (2) Lack of appropriate on-line instrumentation. It is often the case that off-line laboratory tests are the only means of determining product quality measurements. However such laboratory analyses introduce delays in the measurement of key performance indicators. This can result in a significant economic loss if the analysed product fails the quality control test. In such situations an improved monitoring system is therefore required to determine product quality online and minimise commercial wastage. To facilitate this, advanced monitoring and control or optimisation techniques require inferred measurements, generated with correlations from readily available process variables (independent variables). Although inferential models are widely used in industry, only a few techniques for inferential model development are discussed in the open literature. This paper therefore will present a comparative evaluation study of the current inferential measurement techniques. An improved systematic approach for the development of inferential models using intelligent and soft computing systems is also highlighted. The proposed approach is designed to address some of the problems that currently exist in the area of inferential modelling through the fusion of statistical and computational intelligence models. A novel method of fusion is also proposed and an industrial case study is then presented to demonstrate the methodology by inferring the ‘Anchorage’ of polymeric-coated substrates (i.e. Tyvek or paper) in the coating industry. The application on which this methodology is demonstrated is unique. No such work in the literature to date has presented any inferential modelling strategies in the area of the coating industry. This strategy developed through the fusion of statistical and artificial modelling to generate a hybrid inferential measurement system has the potential to significantly improve the quality control monitoring system and reduce the economic loss encountered through the production of off-spec material. 相似文献
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在锅炉燃烧过程的控制中 ,系统常常会受到不可测干扰的影响 ,造成能源浪费和环境污染。其主要问题是燃烧过程的输出量难以测量。对于这一类的过程控制 ,由于扰动及输出量不能测量 ,就不得不采用控制辅助输出量的方法间接控制过程的主要输出量。文章通过对工业锅炉燃烧过程的机理分析与数学建模 ,实现了由可测输出量估计这些干扰对过程的影响 ,并采用推理控制削弱了这种干扰的影响。仿真实验证明了建模分析和推理控制方法是可行的。 相似文献