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1.
基于ISO/IEC17799标准建立了一个综合的信息系统风险分析框架,并运用模糊多准则决策(FMCDM)方法计算信息安全风险,根据风险等级矩阵(RLM)对信息资产风险进行级别划分,最终建立评估信息资产相关风险的完整模型。 相似文献
2.
The estimation of the link capacity and its available bandwidth in an end-to-end path is crucial for network management, admission
control and flow control for adaptive applications. This paper introduces an estimation mechanism able to accurately estimate
the available bandwidth of all links in an end-to-end path, through its capacity and cross-traffic estimation. The estimation
procedures resort to the dispersions of packet pairs and trains using the concepts of ICMP Timestamp and Traceroute that,
efficiently used together, enable the measurement of the dispersions in all links in the path. These mechanisms were evaluated
through simulation experiments, where we analyzed the influence of the several network parameters on each estimation mechanism.
The results show that these estimation methods are able to accurately estimate both the capacity and the cross-traffic of
all links in a path with moderate length and with low overhead. 相似文献
3.
报导一种模糊逻辑控制系统的建模与优化方法。以此方法设计的模糊逻辑控制器,用于双波长稳频CO2激光器的控制得到令人满意的结果。 相似文献
4.
介绍了采用模糊控制技术解决真空冻干生产线控制中大超调量、大滞后等问题的方法 ,详述了模糊控制系统的构成、主要功能和实现方法 相似文献
5.
6.
Inaki Arrazola Agn s Plainfoss Henri Prade Claudette Testemale 《Information Systems》1989,14(6):487-492
This paper presents different approaches which enable a data base management system to obtain a plausible fuzzy estimate for an attribute value of an item for which the information is not explicitly stored in the data base. This can be made either by a kind of analogical reasoning from information about particular items or by means of expert rules which specify the (fuzzy) sets of possible values of the attribute under consideration, for various classes of items. Another kind of expert rules enables the system to compute an estimate from the attribute value of another item provided that, in other respects, this latter item sufficiently resembles the item, the value of which we are interested in; then these expert rules are used either for controlling the analogical reasoning process or for enlarging the scope of application of the first kind of expert rules. The different approaches are discussed in the framework of possibility theory. 相似文献
7.
Takahiro Hoshino 《Computational statistics & data analysis》2008,52(3):1413-1429
The estimation of the differences among groups in observational studies is frequently inaccurate owing to a bias caused by differences in the distributions of covariates. In order to estimate the average treatment effects when the treatment variable is binary, Rosenbaum and Rubin [1983. The central role of the propensity score in observational studies for causal effects. Biometrika 70, 41-55] proposed an adjustment method for pre-treatment variables using propensity scores. Imbens [2000. The role of the propensity score in estimating dose-response functions. Biometrika 87, 706-710] extended the propensity score methodology for estimation of average treatment effects with multivalued treatments.However, these studies focused only on estimating the marginal mean structure. In many substantive sciences such as the biological and social sciences, a general estimation method is required to deal with more complex analyses other than regression, such as testing group differences on latent variables. For latent variable models, the EM algorithm or the traditional Monte Carlo methods are necessary. However, in propensity score adjustment, these methods cannot be used because the full distribution is not specified.In this paper, we propose a quasi-Bayesian estimation method for general parametric models that integrate out the distributions of covariates using propensity scores. Although the proposed Bayes estimates are shown to be consistent, they can be calculated by existing Markov chain Monte Carlo methods such as Gibbs sampler. The proposed method is useful to estimate parameters in latent variable models, while the previous methods were unable to provide valid estimates for complex models such as latent variable models.We also illustrated the procedure using the data obtained from the US National Longitudinal Survey of Children and Youth (NLSY1979-2002) for estimating the effect of maternal smoking during pregnancy on the development of the child's cognitive functioning. 相似文献
8.
9.
1.引言 在人工智能领域中,产生式系统是一种比较有效的知识表示方法,并得到了广泛应用。目前许多较为成功的专家系统都是用产生式系统实现的~[1]。随着应用领域的不断扩士其知识座的抓橄称渐增 相似文献
10.