uncertain reasoning造句

• A reliability analysis for uncertain reasoning with specified tolerance
  模糊推理在特征识别中的应用研究
• All above discussion is to provide suitable foundation and method for uncertain reasoning
  以上的讨论为处理不确定性推理提供了适当的途径。
• The structure model is a nonlinear model in nature , and can be composed of a group of uncertain reasoning rules easily
  这种结构模型是一种本质非线性模型，可以很容易由一组不确定性推理规则构成。
• In the paper , the models of uncertain reasoning are focused , such as the reasoning model of bayes probability , reliability theory , d - s evidence theory and neural network
  本文主要涉及的不确定推理模型包括主观贝叶斯的概率推理模型，可信度理论推理模型，证据理论及其改进推理模型以及神经网络推理模型。
• Artificial intelligence is an important research field and widely concerned in the science of computer . meanwhile , the study of uncertain reasoning is also an active branch and the key technology
  人工智能是计算机科学的一个重要研究领域，受到广泛关注，而人工智能中的推理研究是最为活跃的研究方向与核心技术之一。
• This paper develops a reasoning algorithm special for the combination of predicate presentation and fuzzy knowledge , which effectively solves the conflict between predicate logic and uncertain reasoning
  为了解决谓词不能有效的进行不精确推理的问题,提出了针对谓词结合模糊知识的推理算法,建立了基于谓词的模糊推理系统。
• For uncertain reasons , the former guard of ministry of army , lee yi - yuan beating an italian , an american and a briton near the peking embassy district on april 13 , 1924 , caused a grave international dispute
  1924年4月13日，前陆军部卫兵李义元，因为不明原因在北京使馆区附近地先后殴打了义、美、英三国公民，引起重大国际纠纷。
• By the experience , we can draw the conclusion that every models of uncertain reasoning in the information fusion have different characters , if these models are considered form different applied areas , the conclusion must be acquired differently
  实验表明，利用不同的不确定推理模型，并将之应用于信息融合中，各有优劣，各有独到之处，从不同角度出发考虑推理模型的性能，会得到不同的结论。
• 3 ) after analyzing advantage and disadvantage of neural network and fuzzy reasoning , a project to solve real - time , fault tolerance and uncertain reasoning problems of c3i systems and a data fusion architecture of c3i systems are proposed
  3 )在分析人工神经网络和模糊推理优缺点的基础上，基于互补思想，提出神经网络?模糊推理融合解决方案，以解决c3i数据融合的实时性、容错性和对不确定信息的推理等问题；提出了基于神经网络? ?模糊推理现代c3i数据融合框架。
• In the aspect of the knowledge base structure for the expert system , it has described the matter ’ s former term and consequent according to the production system rule ; on the side of the structure of reasoning machine , i have selected the synthetically reasoning and applied the algorithm of weight uncertain reasoning to have the reasoning analysis to the symptoms of disease
  专家系统在知识库的构造方面以产生式规则描述事件的前项和后项;在推理机的构造上采用混合式推理并应用加权不确定性推理算法对疾病的症状进行推理分析得出结论。
• Based on analyzing of characteristics of current c3i systems and limitations of old c3i systems , neural network and fuzzy reasoning technologies are introduced into c3i data fusion system . moreover , in order to solve real - time , fault tolerance and uncertain reasoning problems of c3i systems , an architecture of c3i systems based on the above new idea is proposed
  本文在深入分析c3i系统特点、原有c3i数据融合的缺陷、以及神经网络和模糊推理优缺点的基础上，基于互补思想，将神经网络? ?模糊推理融合理论引入c3i数据融合系统，构造了基于神经网络? ?模糊推理的c3i数据融合框架，以此解决现代c3i系统中的实时性、容错性和对不确定信息的推理等问题。
• When project financing is used in the developing country ， the cost of the financing is higher than it is in the developed country because of some uncertain reasons . it is showed in the paper that trough completing the management of the risk and distributing the risk reasonable the risk can be decreased
  本文通过规范分析和实证分析相结合的方法分析说明，通过完善项目融资的风险管理，进行合理的风险分配，通过开拓项目融资创新业务，采用适当的风险规避方式，可以降低项目融资的风险。
• After discussing of the current bdar , the chosen radar ’ s damage mode and effects is analyzed in the paper according to its function structure and fighting mission . and then , an expert system is presented to assess effectively and intelligently based upon the bayesian networks . in detail , three knowledge representations , i . e . production rule , frame and bayesian networks are adopted to express different kinds of knowledge in the expert system , and forward deduction and bayesian networks ’ uncertain reason are combined to accomplish the expert system inference process
  本文在总结战场损伤评估与修复的理论体系和研究现状的基础上,选用某型号雷达作为研究对象,按照其功能结构及作战任务的特点,分析了它的战场损伤模式与影响,并就其损伤评估与修复的常用方法和决策思路,设计了一个基于贝叶斯网络的专家系统以提高战损评估决策的自动化、智能化水平。
• Then basing the theory of certainty , a new uncertain reasoning model was introduced and this model was validated in the example of tomato . then , the step of realization of the neural - expert hybrid expert system ' s inference engine was introduced . a diagnose method of diseases and insect pests base on module of neural network was presented and realized in this paper
  在确定性理论的基础上，提出了一种新的不确定性推理模型，以番茄营养诊断为例对这种新的不确定性推理模型进行了验证，同时给出了系统推理过程的实现程序步骤。
• 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。
• This paper researches the asphalt expert ' s thinking pattern and adopts two reasoning model to simulate it . of the two reasoning model , uncertain reasoning based on c - f model simulate the asphalt expert ' s simple and linear thinking , while fuzzy reasoning based on fuzzy theory simulate the asphalt expert ' s fuzzy thinking
  本文研究了沥青路面施工专家的思维模式，并采用了两种推理模型予以模拟，其中，基于c - f模型的不确定推理模拟沥青路面施工专家的简单、线性思维，模糊推理模拟沥青路面施工专家的模糊思维。
• It is this research that overcomes the difficult problems which variable factors in system design are many and researches about their coupling property are few with using engineering - organism - economy united theory , which horticulture facility types are too many , standardization low and dimension diverse with delamination strategy , and which reasoning in decision - making subsystem is hard because rules are uncertain with using uncertain reasoning with weight
  本研究运用工程?生物?经济一体化的理论，解决了系统设计中变量因子多而杂、且相互耦合研究少的难题；运用分层策略，解决了园艺设施类型多、标准化程度低、数量大小参差不齐的难题；在决策分系统中，利用加权的不确定推理，解决了因规则的不确定性而带来得推理机制的难题。