启发式知识

基本解释 (translations)

heuristics

与启发式知识相关的网络例句 [注：此内容来源于网络，仅供参考]

Then, two new algorithms based on conditional entropy, namely CEBARKCC algorithm and CEBARKNC algorithm, are developed in the thesis.

在上述规律的基础上，论文提出了两个新的基于Rough Set理论的启发式知识约简算法：CEBARKCC算法和CEBARKNC算法。

In specialized diaphysis course teaching does guidance with the teaching theory from correcting the relation of the teaching subject and object to set out,and selects heuristic teaching method.

在专业骨干课教学中，从端正教学主体客体出发，以教学理论为指导，采取启发式教学方式，在教学内容的组织过程中及时补充科研动态，拓宽教学知识面的同时突出专业重点，重视对学生专业实践能力的培养，并适应园林专业的新发展，教师作为传授专业知识的载体，应加强专业知识的积累与更新，以保证教学良性循环，培养社会和时代发展需要的专业人才。

Presently, there are two kinds of arithmetic for reduction of knowledge. One is by using discrimination matrix construct discrimination function.

目前求解知识约简的算法主要有两种：一种是利用辨识矩阵构造区分函数，另外一种是基于属性重要性的启发式算法。

On the base of applied tech. and system structure, the key tech. are expressed in detail. It includes:Knowledge representation technology: it is described in two stages by "Depictive frame + Rule group"."Depictive frame" is used to reflect the factors concerning question field."Rule group" reflects the son-question in question field; knowledge management system: it is made up of knowledge-base editing component, factor classifying component, knowledge inspecting component and extractive knowledge component; uncertainty reasoning adopt method of elicitation search strategy and data drive controlled by member knowledge. It take reliability of compound proof at first. That can resolve the matching contradiction. Reasoning explanation introduce pre-text and followed method of resolving path. Knowledge discovery component take SLIQ as basic arithmetic. It provides classification model in two stage forms which aim at training suit. That is decision tree and productive rule.

在确定应用技术与系统结构的基础上，重点阐述了本文的核心技术，这包括：知识表示技术，采用"描述框架+规则组"的层次结构，"描述框架"用于描述问题域所涉及的因素，"规则组"反映问题域内的子问题；知识管理系统，由知识库编辑构件、因素分类构件、知识检测构件和知识求精构件组成；不确定性推理机采用启发式搜索策略，元知识控制的数据驱动，以复合证据可信度优先作为匹配冲突消解的策略，推理解释采用预置文本与求解路径追踪的方法；知识发现，采用SLIQ快速可伸缩算法，分类模型用判定树与产生式规则两种形式描述。

The automatic generated technique of inference rule base is studied from conception base to realize standardization and automation of knowledge base.

研究了归纳学习和指导学习相结合的集成式机器学习算法，实现了基于维修记录库和对专家启发式提问相结合的知识自动获取，大大提高FMS故障诊断专家系统的智能化程度。

Throught adaptive algorithm of network, the system constantly revise right values distribute so as to meet goal. Distribute the heuristic knowledge and the experience knowledge to network interconnection and right value.?The reasoning machine carries on reasoning according to the knowledge that involve in knowledge base and fact that users offer.?Through front computation of nerve network, the output port obtains the output vector.?The explanation module of ES is explained to user.At last, this paper has realized grab hydraulic system based on ANNES intelligent diagnosis, it has proven this fault diagnosis method feasibility.

ANNES的工作过程是：①首先建立知识库；②学习系统获取知识时，它只要求专家提供范例及相应的解，通过神经网络学习算法对样本进行学习，经过网络内部自适应算法不断修改权值分布以达到要求，把专家求解实际问题的启发式知识和经验分布到网络的互连及权值分布上；③推理机根据知识库中的知识和用户提供的事实进行推理；④通过神经网络的前向计算，在输出端获得输出矢量：⑤经专家系

On the base of applied tech. and system structure, the key tech. are expressed in detail. It includes:Knowledge representation technology: it is described in two stages by "Depictive frame + Rule group"."Depictive frame" is used to reflect the factors concerning question field."Rule group" reflects the son-question in question field; knowledge management system: it is made up of knowledge-base editing component, factor classifying component, knowledge inspecting component and extractive knowledge component; uncertainty reasoning adopt method of elicitation search strategy and data drive controlled by member knowledge. It take reliability of compound proof at first. That can resolve the matching contradiction. Reasoning explanation introduce pre-text and followed method of resolving path. Knowledge discovery component take SLIQ as basic arithmetic. It provides classification model in two stage forms which aim at training suit. That is decision tree and productive rule.

在确定应用技术与系统结构的基础上，重点阐述了本文的核心技术，这包括：知识表示技术，采用&描述框架+规则组&的层次结构，&描述框架&用于描述问题域所涉及的因素，&规则组&反映问题域内的子问题；知识管理系统，由知识库编辑构件、因素分类构件、知识检测构件和知识求精构件组成；不确定性推理机采用启发式搜索策略，元知识控制的数据驱动，以复合证据可信度优先作为匹配冲突消解的策略，推理解释采用预置文本与求解路径追踪的方法；知识发现，采用SLIQ快速可伸缩算法，分类模型用判定树与产生式规则两种形式描述。

To overcome the disadvantage of ordered reduction which is based on the discernibility matrix as the time complexity is increscent exponential along with the size of decision tables,the judgment theorem with respect to distribution reduction is obtained,and a heuristic algorithm is proposed.

在不一致决策表中，以知识的包含度为基础，将一致和不一致对象分开，定义了一种新的属性重要性；为克服区分矩阵法时间复杂度随系统大小增加而指数增长的缺陷，给出分布约简的数学判定定理，提出了一种求分布约简的启发式方法。

Perfect knowledge about a domain renders search unnecessary and, likewise, exhaustive search obviates heuristic knowledge.

任何一个领域中的完美理论的建立都意味着一些不必要的探索，同样地，一些详尽的探索也会错过一些启发式的知识。

Based on the content characteristics of the course of fluid mechanics and the learning law,such ways as the interesting real cases,teaching method of qualitative thinking,trial-correcting students' papers by students,intensifying the multimedia teaching and recomposing the teaching contents were used in light of the principle of heuristic teaching.

文章根据流体力学课程的内容特点和学生的学习规律，按照启发式教学原则，通过采用直观有趣的事例、思路式定性教学、让学生试改作业、加强多媒体教学以及对教学内容进行重组整合等多种方式使学生的知识和能力得到全面提高。