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Symbolic representation based on trend features for knowledge discovery in long time series

Hong YIN,Shu-qiang YANG,Xiao-qian ZHU,Shao-dong MA,Lu-min ZHANG

《信息与电子工程前沿（英文）》 2015年第16卷第9期页码 744-758 doi: 10.1631/FITEE.1400376

摘要： The symbolic representation of time series has attracted much research interest recently. The high dimensionality typical of the data is challenging, especially as the time series becomes longer. The wide distribution of sensors collecting more and more data exacerbates the problem. Representing a time series effectively is an essential task for decision-making activities such as classification, prediction, and knowledge discovery. In this paper, we propose a new symbolic representation method for long time series based on trend features, called trend feature symbolic approximation (TFSA). The method uses a two-step mechanism to segment long time series rapidly. Unlike some previous symbolic methods, it focuses on retaining most of the trend features and patterns of the original series. A time series is represented by trend symbols, which are also suitable for use in knowledge discovery, such as association rules mining. TFSA provides the lower bounding guarantee. Experimental results show that, compared with some previous methods, it not only has better segmentation efficiency and classification accuracy, but also is applicable for use in knowledge discovery from time series.

关键词： Long time series Segmentation Trend features Symbolic Knowledge discovery

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基于知识库的知识发现（KDK）的结构模型与挖掘算法研究

杨炳儒,申江涛,陈泓婕

《中国工程科学》 2003年第5卷第6期页码 49-54

摘要：

从知识库中发现新知识KDK（knowledge discovery in knowledgebase）是一个新课题，它的成功将直接作用于大型知识库的构建，并将为解决目前机器学习的瓶颈问题&mdash

关键词：基于知识库的知识发现卡尔纳普归纳逻辑科恩归纳逻辑假设评估

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知识发现系统框架及其理论体系的构造方法论

杨炳儒

《中国工程科学》 2011年第13卷第9期页码 83-91

摘要：

当前知识发现的主流发展是围绕着寻求在各类数据库和应用背景下高性能、高扩展性的挖掘算法这一主题而展开的。事实上有比算法重要的决定挖掘流程的过程模型的研究,还有更为重要的决定模型和算法的内在机理(反映知识发现系统或过程本身规律)的研究,尚未得到应有的重视。笔者另辟蹊径,将所论三者有机地融合与集成,构造了一类基于认知心理特征的自主知识发现“系统框架”,通过对类似的几类“系统框架”的交叉融合、综合集成,构造出基于内在认知机理的知识发现理论体系KDTICM。研究与实验结果表明:这种高起点、高层次的构造方法论研究,有可能形成高效能挖掘系统与新的研究方向;这种构造方法论的研究,可使长时间得不到解决的“领域知识实质性地介入到知识发现过程中”对知识库进行“动态实时维护”等重要问题得以解决;通过揭示知识发现的潜在规律与复杂性,可反作用于主流发展。最后，给出了此种构造方法有效性的有力佐证。

关键词：双库协同机制过程模型KDD* Maradbcm算法系统架构MMAKDS 理论体系KDTICM

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知识发现领域中当今面临的五类重大问题

杨炳儒

《中国工程科学》 2009年第11卷第4期页码 76-83

摘要：

系统地总结与提出知识发现(KD)领域中当今面临的五类重大问题，它们是KD中的两大核心问题、两大猜想问题、主流发展中富有挑战性的问题、应用研究中的相关领域重大问题以及KD技术标准的制定问题，并给出其部分成果或具体分析。这五类问题密切相关，对它们的研究必将KD推向新的发展阶段,并在该领域内外产生深刻的影响。

关键词： KD核心问题 KD猜想 KD挑战性问题蛋白质二级结构预测 KD技术标准

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一种基于制造大数据的产品工艺自适应设计方法

魏巍,陈政,袁君

《中国工程科学》 2020年第22卷第4期页码 42-49 doi: 10.15302/J-SSCAE-2020.04.017

摘要：

随着数字化与智能化生产方式在制造业中的广泛应用，引导企业重视并发挥制造大数据的价值对革新产品工艺设计具有重要意义。本文旨在面向企业数据与业务深度融合的应用需求，提出一种基于制造大数据挖掘的产品工艺自适应设计应用方法，用于解决企业中制造数据利用率不足等问题。以企业制造数据为起点，提出了“数据 + 知识 + 决策”的产品工艺自适应设计模式，总结了该模式的制造数据挖掘与利用流程，涵盖多源异构数据融合、数据清洗与预处理、数据变换与降维、数据挖掘、数据可视化和设计决策6个过程。最后以汽车产品焊接工艺为例，建立焊接工艺参数与焊接缺陷的预测模型，用于改善焊接工艺并提高焊接质量，实现制造大数据驱动的焊接工艺自适应设计。研究表明，制造大数据蕴含丰富的知识与模式，可以指导产品设计决策，支持实现不同制造环境下的产品工艺自适应设计；建议进一步推动大数据与第五代移动通信技术等新兴技术的结合，增加对大数据平台、算法设计平台研发的投入，激发制造大数据与产品工艺设计的更大交融。

关键词：产品工艺，自适应设计，制造大数据，数据挖掘，知识发现

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HIGH-PERFORMANCE COMPUTATION AND ARTIFICIAL INTELLIGENCE IN PESTICIDE DISCOVERY: STATUS AND OUTLOOK

《农业科学与工程前沿（英文）》 2022年第9卷第1期页码 150-154 doi: 10.15302/J-FASE-2021419

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Standard model of knowledge representation

Wensheng YIN

《机械工程前沿（英文）》 2016年第11卷第3期页码 275-288 doi: 10.1007/s11465-016-0372-3

摘要：

Knowledge representation is the core of artificial intelligence research. Knowledge representation methods include predicate logic, semantic network, computer programming language, database, mathematical model, graphics language, natural language, etc. To establish the intrinsic link between various knowledge representation methods, a unified knowledge representation model is necessary. According to ontology, system theory, and control theory, a standard model of knowledge representation that reflects the change of the objective world is proposed. The model is composed of input, processing, and output. This knowledge representation method is not a contradiction to the traditional knowledge representation method. It can express knowledge in terms of multivariate and multidimensional. It can also express process knowledge, and at the same time, it has a strong ability to solve problems. In addition, the standard model of knowledge representation provides a way to solve problems of non-precision and inconsistent knowledge.

关键词： knowledge representation standard model ontology system theory control theory multidimensional representation

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知识论框架通向信息-知识-智能统一的理论

钟义信

《中国工程科学》 2000年第2卷第9期页码 50-64

摘要：

知识是人类所创造的宝贵财富，但至今没有形成系统的知识理论。文章旨在提出和建立知识论的框架体系，包括它的基础和主体两部分。基础部分主要给出知识的概念、定义、表示、度量、推理和决策规则；主体部分的核心是阐明由信息提炼知识（知识生成）以及由知识形成智能（知识激活）的机理。知识论的建立将为信息论-知识论-智能论的统一理论奠定坚实的基础，促进人们在更高的水平上利用信息和知识，研究、设计和应用各种智能机器，推动经济和社会的发展。

关键词：知识知识量知识生成知识激活信息-知识-智能的统一理论

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Liquid metal material genome: Initiation of a new research track towards discovery of advanced energy

Lei WANG, Jing LIU

《能源前沿（英文）》 2013年第7卷第3期页码 317-332 doi: 10.1007/s11708-013-0271-9

摘要： As the basis of modern industry, the roles materials play are becoming increasingly vital in this day and age. With many superior physical properties over conventional fluids, the low melting point liquid metal material, especially room-temperature liquid metal, is recently found to be uniquely useful in a wide variety of emerging areas from energy, electronics to medical sciences. However, with the coming enormous utilization of such materials, serious issues also arise which urgently need to be addressed. A biggest concern to impede the large scale application of room-temperature liquid metal technologies is that there is currently a strong shortage of the materials and species available to meet the tough requirements such as cost, melting point, electrical and thermal conductivity, etc. Inspired by the Material Genome Initiative as issued in 2011 by the United States of America, a more specific and focused project initiative was proposed in this paper—the liquid metal material genome aimed to discover advanced new functional alloys with low melting point so as to fulfill various increasing needs. The basic schemes and road map for this new research program, which is expected to have a worldwide significance, were outlined. The theoretical strategies and experimental methods in the research and development of liquid metal material genome were introduced. Particularly, the calculation of phase diagram (CALPHAD) approach as a highly effective way for material design was discussed. Further, the first-principles (FP) calculation was suggested to combine with the statistical thermodynamics to calculate the thermodynamic functions so as to enrich the CALPHAD database of liquid metals. When the experimental data are too scarce to perform a regular treatment, the combination of FP calculation, cluster variation method (CVM) or molecular dynamics (MD), and CALPHAD, referred to as the mixed FP-CVM-CALPHAD method can be a promising way to solve the problem. Except for the theoretical strategies, several parallel processing experimental methods were also analyzed, which can help improve the efficiency of finding new liquid metal materials and reducing the cost. The liquid metal material genome proposal as initiated in this paper will accelerate the process of finding and utilization of new functional materials.

关键词： liquid metal material genome energy material material discovery advanced material room-temperature liquid alloy thermodynamics phase diagram

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An econometric investigation using price discovery theory

Yeli ZENG, Cong DONG, Mikael HÖÖK, Jinhua SUN, Danyang SHI

《能源前沿（英文）》 2020年第14卷第4期页码 726-739 doi: 10.1007/s11708-020-0701-4

摘要： China became the world’s second largest liquefied natural gas (LNG) importer in 2018 but has faced extremely high import costs due to a lack of bargaining power. Assessments of the Shanghai LNG Price Index, first released in 2015, are vital for improving the understanding of these cost dynamics. This paper, using the LNG price index data from the Shanghai Petroleum and Gas Exchange (SHPGX) coupled with domestic and international LNG prices from July 1, 2015 to December 31, 2018, estimates several econometric models to evaluate the long-term and short-term equilibriums of the Shanghai LNG Price Index, the responses to market information shocks and the leading or lagging relationships with LNG and alternative energy prices from other agencies. The results show that the LNG price index of the SHPGX has already exhibited a long-term equilibrium and short-term adjustment mechanisms to reflect the average price level and market movements, but the market information transparency and price discovery efficiency of the index are still inadequate. China’s LNG market is still relatively independent of other natural gas markets, and marketization reforms are under way in China. The influence of the SHPGX LNG price index on the trading decisions of market participants is expected to improve with further development of China’s LNG reforms, the formation of a natural gas entry-exit system, and the increasing liquidity of the hub.

关键词： liquefied natural gas price index Shanghai Petroleum and Gas Exchange price discovery market reforms

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Research on Knowledge Sharing and Transfer in Remanufacturing Engineering Management Based on SECI Model

Ling-ling Zhang,Ming-hui Zhao,Qiao Wang

《工程管理前沿（英文）》 2016年第3卷第2期页码 136-143 doi: 10.15302/J-FEM-2016030

摘要： In this paper, an application mode and method of knowledge management in remanufacturing engineering management is established based on Nonaka’s SECI model. The relationships between knowledge transfer, knowledge sharing and remanufacturing engineering management are highlighted. It is noticeable that a great deal of knowledge transfer and sharing activities, which can improve the performance of remanufacturing engineering management constantly, are involved in remanufacturing engineering.

关键词： remanufacturing engineering management knowledge transfer and sharing knowledge management

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perspectives and future research directions for the phytoremediation of heavy metal-contaminated soil: A knowledge

《环境科学与工程前沿（英文）》 2022年第16卷第6期 doi: 10.1007/s11783-021-1507-2

摘要：

• The overall global perspective of the PHMCS field was obtained.

关键词： Heavy metal-contaminated soil Hot topics Knowledge mapping analysis Knowledge base Phytoremediation

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知识管理系统的运用与深化

李华

《中国工程科学》 2011年第13卷第8期页码 87-93

摘要：

在知识经济时代，企业已经开始认识到最宝贵的资产是知识，知识不但是生产的关键要素，而且还是企业保持持续竞争优势的重要手段。企业知识管理系统的有效实施，要在正确的思想指导下，建立适于知识共享的组织结构和企业文化，在理解和实施知识管理时必须坚持积累、信任、共享、交流、学习五项原则。知识管理的目标是实现组织总体发展战略，因此知识共享的过程也必须以实现组织战略目标为前提，重视对共享知识的甄选，建立知识共享平台和存储管理单元，引导知识交流，实施奖励政策。

关键词：知识管理知识共享知识论坛

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关键技术的突破促进塔里木气区的发现

邱中建

《中国工程科学》 2000年第2卷第9期页码 38-41

摘要：

塔里木气区包括塔北一库车气区和塔西南气区两大部份。塔北一库车气区已成为我国最大的天然气富集区之一，该气区北部存在着特大型气田，但地势陡峻，地质结构复杂，长期以来是勘探工作的禁区。经过近十年的系统攻关，关键技术获得重要进展：一是山地地震勘探取得突破；二是综合地质研究取得新认识；三是复杂地质条件下的钻探取得成功。

这些技术促使库车地区天然气勘探获得大进展，并发现了克拉2号特大型气田，探明储量2506×10⁸m³,是“西气东输”的主力气田。目前，塔里木气区已探明天然气储量4688×10⁸m³(16.5TCF)，对“西气东输”项目的启动做出了重要贡献。

关键词：关键技术突破发现塔里木气区

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大数据知识工程发展现状及展望

郑庆华,刘欢,龚铁梁,张玲玲,刘均

《中国工程科学》 2023年第25卷第2期页码 208-220 doi: 10.15302/J-SSCAE-2023.02.018

摘要：

大数据知识工程是人工智能的“基础设施”、诸多行业和领域面临的共性需求、信息化迈向智能化的必由之路。本文阐述了大数据知识工程产生的背景与概念内涵，提出了“数据知识化、知识体系化、知识可推理”的研究框架；梳理了知识获取与融合、知识表征、知识推理等大数据知识工程关键技术和智慧教育、税务风险管控、智慧医疗等典型场景中的工程应用；总结了大数据知识工程面临的挑战，研判了大数据知识工程的未来研究方向，包括复杂大数据知识获取、知识+数据混合学习、脑启发知识编码记忆等。研究建议，引导多学科交叉融合，设立重大和重点研发专项，推动大数据知识工程基础理论与技术攻关；加强企业和研究机构间交流合作，推广前沿研究成果并形成应用示范，建立大数据知识工程行业标准体系；以重大需求应用为导向，探索校企协同育人模式，加快大数据知识工程技术在重要行业的落地应用。

关键词：大数据知识工程知识获取知识融合知识表征知识推理