电子线路课程教学的整体优化研究

根据电子线路课程的特点,结合多年电子线路的教学经验,从培养动手型和创新型人才的角度出发,本文提出了对电子线路教学进行整体优化的一些方法。将电子线路课程的整个教学环节进行整体优化,特别是对教学过程中的实验环节提出了具体的优化措施。提出了多媒体教学的优缺点和传统教学方式相结合的必要性。要求学生掌握基础知识的同时,重点培养他们的分析能力、综合应用能力、设计能力和创新意识。     

中国耕地细碎化的理论解析与研究框架

基于演绎推理法和文献研究法,探索耕地细碎化的概念、过程、机制和效应,并构建耕地细碎化研究框架,为耕地细碎化研究提供理论指导。结果表明:①耕地细碎化是耕地在自然-人为双重因素驱动下,耕地地块在形态上不断分割、变小,耕地产权在主体上不断细分、多元的过程,并分别表现为相互关联又有所区别的耕地景观细碎化和耕地权属细碎化; ②耕地细碎化研究应遵循“诊断-机制-效应-治理”的理论框架,耕地细碎化诊断需从形态和权属两方面构建评价指标体系,形成机制可从自然切割力、利用切割力、设施切割力和管理切割力4个方面揭示不同因素的作用机制,效应需揭示不同尺度下耕地细碎化形态和产权的趋势性转折对经济、社会和生态的影响,治理研究应按照“问题识别治理潜力治理路径保障措施”的逻辑顺序构建。     

基于量化规则格的关联规则渐进更新*

提出一种基于量化规则格的规则更新算法,重点讨论了在新增格节点的过程中规则更新的思想,实现在格的渐增生成过程中,相应的关联规则也得到渐进更新.最后给出简单实例说明规则更新算法的正确性.     

TRIZ理论中物质-场的不同应用

通过对飞机发动机机罩概念设计中的物-场分析，简要概括了在实际的概念设计中应该如何应用和把握物质-场分析的侧重点。     

一种混合的领域概念分类体系自动构建算法

领域概念分类体系自动构建在人工智能、自然语言处理和信息检索等领域具有重要作用,但现有研究较多关注通用知识,面向特定领域的研究较少,且存在领域概念间关系抽取准确率以及自动构建算法效率较低等问题。为此,提出一种混合的领域概念分类体系自动构建算法,该算法主要包括领域概念间关系抽取模块和分类体系构建模块。领域概念间关系抽取模块设计考虑中文自身的特点,采取句法树和基于规则相结合的方法,以提高抽取领域概念间关系的查准率和查全率;分类体系构建模块设计采取改进的BRT算法,从而在降低算法复杂度的同时,提高领域分类体系构建的查准率。在通信、金融和计算机领域的实验结果均表明,与BRT算法相比,该算法的构建效果较好,查准率最高可达到89.3%。     

Ontology-based similarity for product information retrieval

Product development of today is becoming increasingly knowledge intensive. Specifically, design teams face considerable challenges in making effective use of increasing amounts of information. In order to support product information retrieval and reuse, one approach is to use case-based reasoning (CBR) in which problems are solved “by using or adapting solutions to old problems.” In CBR, a case includes both a representation of the problem and a solution to that problem. Case-based reasoning uses similarity measures to identify cases which are more relevant to the problem to be solved. However, most non-numeric similarity measures are based on syntactic grounds, which often fail to produce good matches when confronted with the meaning associated to the words they compare. To overcome this limitation, ontologies can be used to produce similarity measures that are based on semantics. This paper presents an ontology-based approach that can determine the similarity between two classes using feature-based similarity measures that replace features with attributes. The proposed approach is evaluated against other existing similarities. Finally, the effectiveness of the proposed approach is illustrated with a case study on product–service–system design problems.     

基于NB35047-2015规范的锦屏拱坝抗震复核

能源行业标准《水电工程水工建筑物抗震设计规范》(NB35047-2015)已于2015年9月1日颁布实施。介绍了依据该规范开展的锦屏一级高拱坝抗震安全复核工作。主要内容包括:基于设定地震的场地相关设计反应谱研究;采用动力拱梁分载法、线弹性有限元法和非线性有限元法,进行设计和最大可信地震作用下的应力和坝肩岩体动力稳定分析;在选定的人工地震波基础上,采用以基岩峰值加速度在设计地震基础上比例放大的方式,进行大坝地基系统在超设计地震荷载下的地震超载能力分析。复核分析表明,锦屏一级高拱坝具有较高的抗震潜力;设计地震和最大可信地震作用下,坝体抗压强度安全满足现行抗震规范要求,且抗压强度安全有较大安全裕度,坝体拉应力基本未超过混凝土容许的应力范围,仅局部应力集中部位拉应力较大,能满足校核地震作用下"不溃坝"的设防要求。     

An approach for selecting seed URLs of focused crawler based on user-interest ontology

Seed URLs selection for focused Web crawler intends to guide related and valuable information that meets a user's personal information requirement and provide more effective information retrieval. In this paper, we propose a seed URLs selection approach based on user-interest ontology. In order to enrich semantic query, we first intend to apply Formal Concept Analysis to construct user-interest concept lattice with user log profile. By using concept lattice merger, we construct the user-interest ontology which can describe the implicit concepts and relationships between them more appropriately for semantic representation and query match. On the other hand, we make full use of the user-interest ontology for extracting the user interest topic area and expanding user queries to receive the most related pages as seed URLs, which is an entrance of the focused crawler. In particular, we focus on how to refine the user topic area using the bipartite directed graph. The experiment proves that the user-interest ontology can be achieved effectively by merging concept lattices and that our proposed approach can select high quality seed URLs collection and improve the average precision of focused Web crawler.     

云模型在测井曲线分层中的应用

针对由模糊信息导致测井曲线人工分层的不准确,提出了一种基于云模型的测井曲线自动分层方法.而云模型能同时体现概念的随机性和模糊性,利用云变换从测井曲线中提取定性概念,然后对提取的概念进行概念跃升,使得算法输出的概念层次更符合实际.实验表明,该方法能够较准确地提取和表征定性概念,所提取的概念中心与传统测井曲线分层方法得到的概念中心吻合较好,验证了算法的有效性,提高了测井曲线分层的准确性.