fiducial inference

fiducial inference的基本解释

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信念推断

与fiducial inference相关的网络例句 [注：此内容来源于网络，仅供参考]

Finally, the Fiducial inference for the parameter's functions of exponential distribution based on the type Ⅱ censoring observations is given. Simulation study shows that the Fiducial inference is quite accurate.

本文最后还讨论了指数分布在定时截尾情形下参数函数的Fiducial推断问题；并进行了模拟研究，结果表明推断精度很高。

To avoid the collision accidents of ships at sea, with the universalizing and application of computer, and the development and maturity of the technology of Expert System and Artificial Intelligent, this paper developed an intelligent collision avoidance expert system for navigation. The main research work centers on several aspects, which will be represented as below:By the navigation rules" understanding and analyzing, and by the navigation experience and navigation samples" collecting and trimming, we put forth and build a multi-unit and layering KB systematic structure, and implement the KBM. According to features of different knowledge, we adopt multifarious KR, such as: frame KR, production rule KR, procedure KR. We also build a multi-inference system, which based on analog inference, forward illation inference, conversion inference and meta-rule inference. At the same time, we develop each reasoning algorithm. For some problems in collision avoidance region during the building of the expert system, we put forth and build a set of models to solve them using neural network technology.

为了避免船舶间碰撞事故的发生，结合计算机技术在各类船舶中的普及与应用、专家系统技术及人工智能技术的发展、成熟，本文研制、开发了一种具有一定智能的航海避碰专家系统，主要内容包括以下几个方面：通过对航海规则的理解与分析，对航海经验、航海实例的搜集、整理，提出并建立起了航海避碰专家系统的多元分层知识库体系结构，并实现了知识库的管理；根据不同知识的特点，分别采用了框架、产生式规则、过程等多种知识表示方法；提出了一种基于类比推理、正向演绎推理、换位推理及元级推理等的多种推理机制，并建立起了相应的推理算法；引入神经网络技术，针对在建立专家系统过程中所遇到的有关避碰领域内的一些难题，提出并建立了相应解决问题的模型，其中包括：船舶类型的识别，会遇态势的分类及避碰危险的评估。

A new knowledge acquirement way is presented based on the reliability data of product, then the fuzzy semantic net which consists of FEPM and fuzzy fault tree is regard as fault knowledge representation. The formalization of the fuzzy semantic net is described, and the relative concepts and relations are summarized. A stereo-knowledge representation which consisted of FFTF, rule and fuzzy neural network which make up of the shallow knowledge of the product is presented. The integrated fault diagnosis method based on the stereo-knowledge representation is suggested. The method is as follows. The fuzzy search inference is carried out on FFTF firstly. If the node being diagnosing can be decided if it failed or not in the fuzzy search inference, the rule inference to the node is carried out with the rules which being in symptom-fault way. An equivalent method, pattern recognization inference using fuzzy neural network, can fulfill the same work.

提出了以FFTF模糊语义网络为主、基于浅知识的产生式规则、模糊神经网络为辅的产品故障知识的立体知识表示方式，并提出了基于该多种知识表示的综合性故障诊断方法，即：首先对故障产品进行基于FFTF模糊语义网络的模糊搜索推理，如果在模糊搜索推理过程中不能确定当前诊断节点故障与否，则对当前诊断节点进行基于征兆-故障形式的验证式规则推理或者对包含该诊断节点的部件／子系统进行基于模糊神经网络的模式识别推理，如果在完成或者不再进行基于模糊语义网络的故障推理，仍然不能诊断出故障节点，则对基于模糊语义网络诊断过程中形成的故障诊断子图进行神经网络推理。

与fiducial inference相关的网络解释 [注：此内容来源于网络，仅供参考]

fiducial inference：置信推理

fiducial estimation 置信估计 | fiducial inference 置信推理 | fiducial limit 置信限

fiducial inference：信任推论

Feedback mechanism 回馈机制 | Fiducial inference 信任推论 | Fiducial probability 信任机率

fiducial inference：信念推断

信念区间|fiducial interval | 信念推断|fiducial inference | 信念限|fiducial limit

fiducial inference：置信推论

置信分布 fiducial distribution | 置信推论 fiducial inference | 置信(界)限 fiducial limits