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Chinese translation for "bay networks"

贝网络公司

Related Translations:
baies:  巴耶什伯耶什
bayes:  巴耶斯贝斯贝叶斯
bays:  贝斯磁场水平分量曲线的顶底点海湾
bay:  n.1.(比 gulf 小、比 cove 大的)湾,海湾。2.(山中的)凹地。3.【火箭】凹槽;盘,舱。4.【英军】战壕通路。短语和例子Hudson bay 哈德逊湾。 the bay of Bengal 孟加拉湾。n.1.(猎犬等追捕猎物时的)吠声。2.绝境,穷途末路(尤指走投无路时反噬的状态)。短语和例子be at bay 1. 走投无路;被包围,被遏制。 2. 作困兽
Example Sentences:
1.Bayes network is a new inference and express method of uncertain knowledge
摘要贝叶斯网络是不确定性知识表达与推理的一种新方法。
2.This paper addressed bayes network ' s basic theory , methods and applications , finally pointed out its major problems at present
本文论述了贝叶斯网络的基本理论、方法和应用,并指出当前所存在的主要问题。
3.He joined nortel in 1999 before that time , he once served in sun microsystem , bay networks and automated system hong kong limited since 1994
他从1999年加入北电,之前曾在sun 、贝网络、香港自动化公司任职。
4.In this capacity , he successfully merged and integrated the company with bay networks japan , whose parent company had been acquired by northern telecom , and was later re - named nortel networks japan
他在担任此职务时,成功将公司和日本bay networks子公司其母公司已被northern telecom买下合并整合,随后更名为日本nortel networks 。
5.However , because bayes network structure learning algorithm generally explore too big a search space , as well as its computing complexity , and moreover , the such learning algorithm is very easy to fall into the local optimal solution , ban ’ s efficiency is questioned . finding a kind of highly effective global searching algorithm is an extremely important to the study of ban
针对这种分类器的结构学习,设计了结合对数似然的适应度函数,并给出了网络结构的编码方案,设计了相应的遗传算子,使得该算法能够收敛到全局最优的结构。实验结果表明,该算法具有良好的分类效果。
6.In the fourth chapter , we analyze bayes networks - ihe theory of uncertain reasoning . and it is imported into intelligent fault diagnosis and task decomposition process for complicated equipment . the method have some advantage , such as reasoning in two - way ( effect and result ) , diagnosis based on model , and using experts knowledge
利用建模理论中的模型分解理论,建立复杂装备内部各组成部件间的连接关系及层次关系,确定出装备内部的信息传播路径,并建立装备的概率模型,为基于bayesnetworks的不确定性推理及诊断任务的分解奠定了基础。
7.Thirdly , this paper gives out a method of discovering markov blanket of multi - sets rather singleton , and proves the correctness of the method , afterwards this paper expresses it using bayes network too . finally , aimed at the application of educational evaluation , this paper performs post - processing at those rules mined by apriori algorithm , and filters those rules with the constraints of conditional independences , and reads out conditional independences from rules
面向教育评估系统中的具体应用,本文提出了对原有系统中采用的apriori算法挖掘的关联规则进行后处理的方法:采用条件独立性和传统支持度- - -可信度框架相结合的方法进行关联规则的过滤,并从中发现存在的条件独立性限制。
8.In the fifth chapter , we set up knowledge model , node - calculation model on the basis of bayes networks theory , and demarcate task model , build up distributed cooperation diagnosis model based multi - agent technology . the function module of agent is defined clearly , the information propagated in each module and relations among each module are analyzed in details
第三,围绕不确定性诊断问题进行了深入的研究,对bayesnetworks理论进行了全面分析,并将其引入复杂装备的故障诊断中,建立了基于bayesnetworks的推理诊断知识模型、节点计算模型,建立了基于任务的功能划分和组件化多agent协作系统。
9.Classification has always been a central issue on data mining , machine learning and pattern recognition , classifier , as an important model and method of machine learning and data mining , is very important to the development and application of machine learning and the data mining . the classifier ’ s effect closely correlates with the characteristic of data sets , at present , the construction of classifier is generally based on the character of different datasets , there is no such a classifier which is suitable for any data sets . under uncertain conditions , the bayes network is a powerful tools for the knowledge expression and inference , but for difficulties in constructing its network structure and very high time complexity , it has not been considered as a classifier algorithm until the emergence of na ? ve - bayes classifier
分类一直是数据挖掘、机器学习和模式识别等研究的核心问题,贝叶斯网络是作为知识表示和推理的强大工具,由于搜索空间巨大和学习困难的原因,直到朴素贝叶斯理论的出现才被作为分类器算法,改进朴素贝叶斯分类器是贝叶斯分类器学习的一个主要的研究方向。遗传算法本质上是一种求解问题的高效并行全局搜索算法,适合应用于那些改进的分类器的结构学习中。本文提出了一种基于遗传算法的ban分类器算法。
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