Through analyzing influence of various factors on spatial form of campus, the author proposed from the perspective of knowledge science that orientation and mode of knowledge activities play a decisive role in the spa...Through analyzing influence of various factors on spatial form of campus, the author proposed from the perspective of knowledge science that orientation and mode of knowledge activities play a decisive role in the spatial form evolution of campus, and then demonstrated the viewpoint by elaborating spatial form evolution history of campuses of different ages in different regions. On this basis, the future development trend of campus form in the information era was explored.展开更多
The paper examines the three stages of the evolution of national innovation systems: national technology innovation systems, national innovation systems and national knowledge innovation systems. A national knowledge ...The paper examines the three stages of the evolution of national innovation systems: national technology innovation systems, national innovation systems and national knowledge innovation systems. A national knowledge innovation system is a network of institutions and organizations which jointly or individually contributes to the knowledge innovation (including scientific and technical knowledge innovation). The author stresses that knowledge innovation will occur in all processes of the produc-tion, transmission and use of knowledge. There are four subsystems in this system: scientific knowledge innovation, technical knowledge innovation, knowledge trans-mission and knowledge use subsystem. The author also lists some indicators for the System.展开更多
Differences in knowledge regimes and growth dynamics amongst four ideal types of knowledge based firms are analyzed. Two aspects of technological knowledge, technological opportunity and appropriability are traditiona...Differences in knowledge regimes and growth dynamics amongst four ideal types of knowledge based firms are analyzed. Two aspects of technological knowledge, technological opportunity and appropriability are traditionally seen as vital to understand the incentives for research and development activities in firms. However, they do not fully define the technology regimes, when one asks how the knowledge based firm competes. Therefore, the dynamic nature of firm capabilities and knowledge development in terms of expansion and in terms of deepening are also discussed. These two additional aspects of knowledge implies that even if all firms in an industry can be considered to be knowledge intensive these firms do also differ. Using cases of entrepreneurial start-up firms in Sweden, we illustrate whether our conceptual ideas of knowledge development help us understand the diversity and contradictions of firm evolution. Our finding is that firm evolution and capability development is dependent upon both the potential for expanding knowledge, such as by innovations, and by deepening the understanding within established knowledge, such as by learning. This implies that the shaping of a science based industry must be seen in relation both to the value of current knowledge and capabilities together with the sometimes only limited and temporarily advantages of radical innovations.展开更多
Due to the many types of distributed denial-of-service attacks(DDoS)attacks and the large amount of data generated,it becomes a chal-lenge to manage and apply the malicious behavior knowledge generated by DDoS attacks...Due to the many types of distributed denial-of-service attacks(DDoS)attacks and the large amount of data generated,it becomes a chal-lenge to manage and apply the malicious behavior knowledge generated by DDoS attacks.We propose a malicious behavior knowledge base framework for DDoS attacks,which completes the construction and application of a multi-domain malicious behavior knowledge base.First,we collected mali-cious behavior traffic generated by five mainstream DDoS attacks.At the same time,we completed the knowledge collection mechanism through data pre-processing and dataset design.Then,we designed a malicious behavior category graph and malicious behavior structure graph for the characteristic information and spatial structure of DDoS attacks and completed the knowl-edge learning mechanism using a graph neural network model.To protect the data privacy of multiple multi-domain malicious behavior knowledge bases,we implement the knowledge-sharing mechanism based on federated learning.Finally,we store the constructed knowledge graphs,graph neural network model,and Federated model into the malicious behavior knowledge base to complete the knowledge management mechanism.The experimental results show that our proposed system architecture can effectively construct and apply the malicious behavior knowledge base,and the detection capability of multiple DDoS attacks occurring in the network reaches above 0.95,while there exists a certain anti-interference capability for data poisoning cases.展开更多
Due to the insufficiency of utilizing knowledge to guide the complex optimal searching, existing genetic algorithms fail to effectively solve excavator boom structural optimization problem. To improve the optimization...Due to the insufficiency of utilizing knowledge to guide the complex optimal searching, existing genetic algorithms fail to effectively solve excavator boom structural optimization problem. To improve the optimization efficiency and quality, a new knowledge-based real-coded genetic algorithm is proposed. A dual evolution mechanism combining knowledge evolution with genetic algorithm is established to extract, handle and utilize the shallow and deep implicit constraint knowledge to guide the optimal searching of genetic algorithm circularly. Based on this dual evolution mechanism, knowledge evolution and population evolution can be connected by knowledge influence operators to improve the conflgurability of knowledge and genetic operators. Then, the new knowledge-based selection operator, crossover operator and mutation operator are proposed to integrate the optimal process knowledge and domain culture to guide the excavator boom structural optimization. Eight kinds of testing algorithms, which include different genetic operators, arc taken as examples to solve the structural optimization of a medium-sized excavator boom. By comparing the results of optimization, it is shown that the algorithm including all the new knowledge-based genetic operators can more remarkably improve the evolutionary rate and searching ability than other testing algorithms, which demonstrates the effectiveness of knowledge for guiding optimal searching. The proposed knowledge-based genetic algorithm by combining multi-level knowledge evolution with numerical optimization provides a new effective method for solving the complex engineering optimization problem.展开更多
Short-term forecasting is a difficult problem because of the influence of non-linear factors and irregular events.A novel short-term forecasting method named TIK was proposed,in which ARMA forecasting model was used t...Short-term forecasting is a difficult problem because of the influence of non-linear factors and irregular events.A novel short-term forecasting method named TIK was proposed,in which ARMA forecasting model was used to consider the load time series trend forecasting,intelligence forecasting DESVR model was applied to estimate the non-linear influence,and knowledge mining methods were applied to correct the errors caused by irregular events.In order to prove the effectiveness of the proposed model,an application of the daily maximum load forecasting was evaluated.The experimental results show that the DESVR model improves the mean absolute percentage error(MAPE) from 2.82% to 2.55%,and the knowledge rules can improve the MAPE from 2.55% to 2.30%.Compared with the single ARMA forecasting method and ARMA combined SVR forecasting method,it can be proved that TIK method gains the best performance in short-term load forecasting.展开更多
Traditional information systems are passive, i.e., data or knowledge is created, retrieved, modified, updated, and deleted only in response to operations issued by users or application programs, and the systems only c...Traditional information systems are passive, i.e., data or knowledge is created, retrieved, modified, updated, and deleted only in response to operations issued by users or application programs, and the systems only can execute queries or transactions explicitly submitted by users or application programs but have no ability to do something actively by themselves. Unlike a traditional information system serving just as a storehouse of data or knowledge and working passively according to queries or transactions explicitly issued by users and application programs, an autonomous evolutionary information system serves as an autonomous and evolutionary partner of its users that discovers new knowledge from its database or knowledge base autonomously, cooperates with its users in solving problems actively by providing the users with advices, and has a certain mechanism to improve its own state of “knowing” and ability of “working”. This paper seminally defines what is an autonomous evolutionary information system, explain why autonomous evolutionary information systems are needed, and presents some new issues, fundamental considerations, and research directions in design and development of autonomous evolutionary information systems.展开更多
The growth and evolution of domain knowledge have always been the focus of Library and Information Science.Exploring the emergence of correlations in the process of knowledge growth with network science thinking can r...The growth and evolution of domain knowledge have always been the focus of Library and Information Science.Exploring the emergence of correlations in the process of knowledge growth with network science thinking can reveal the growth patterns and mechanisms of knowledge correlations.展开更多
气候问题日趋严重,“双碳”目标引起学者的广泛关注。为分析当前国内外“双碳”领域研究前沿与热点差异,本文利用科学计量技术,针对知网和Web of Science核心数据集自2009—2022年有关“双碳”目标的文献进行时空维度内文献分布特征分...气候问题日趋严重,“双碳”目标引起学者的广泛关注。为分析当前国内外“双碳”领域研究前沿与热点差异,本文利用科学计量技术,针对知网和Web of Science核心数据集自2009—2022年有关“双碳”目标的文献进行时空维度内文献分布特征分析和研究前沿与热点动态演化分析。结果表明:“双碳”领域正处于研究浪潮阶段,自2020年后“双碳”领域发文量呈爆发式增长,研究力量集中于西方发达国家。研究侧重点存在差异,国外“双碳”领域从生物质和太阳能利用等技术角度展开研究,国内则侧重政策治理层面,低碳转型成为研究热点。本文提出“双碳”领域未来发展方向将聚焦于低碳技术和模式创新,以创新助推低碳转型。展开更多
以中国知网(CNKI)和Web of Science为数据源,以智能建造领域2000—2023年期间的高质量文献为对象,借助CiteSpace对筛选出的中外文献进行分析,探讨智能建造当前的研究热点及其演进趋势。结果表明:研究主题方面,中外文献均围绕信息化展开...以中国知网(CNKI)和Web of Science为数据源,以智能建造领域2000—2023年期间的高质量文献为对象,借助CiteSpace对筛选出的中外文献进行分析,探讨智能建造当前的研究热点及其演进趋势。结果表明:研究主题方面,中外文献均围绕信息化展开;研究热点方面,中文文献从研究对象、智能建造技术及研究内容等多种视角开展研究,外文文献重点关注数字化技术在建设项目全生命周期的应用;热点演进趋势方面,中文文献划分为信息化引入、信息化与数智化的初步探索、数字化与绿色智能化的全面应用三个阶段,外文文献可分为技术与理论初探、信息化与自动化、数字化与智能化三个阶段,总体上,中文文献的研究在学习和借鉴外文文献研究的过程中不断深化与成熟,且绿色智能化是未来的研究焦点。展开更多
基金Supported by National Natural Science Foundation "On Planning Concepts of Modern Chinese Campuses" (51108308)
文摘Through analyzing influence of various factors on spatial form of campus, the author proposed from the perspective of knowledge science that orientation and mode of knowledge activities play a decisive role in the spatial form evolution of campus, and then demonstrated the viewpoint by elaborating spatial form evolution history of campuses of different ages in different regions. On this basis, the future development trend of campus form in the information era was explored.
文摘The paper examines the three stages of the evolution of national innovation systems: national technology innovation systems, national innovation systems and national knowledge innovation systems. A national knowledge innovation system is a network of institutions and organizations which jointly or individually contributes to the knowledge innovation (including scientific and technical knowledge innovation). The author stresses that knowledge innovation will occur in all processes of the produc-tion, transmission and use of knowledge. There are four subsystems in this system: scientific knowledge innovation, technical knowledge innovation, knowledge trans-mission and knowledge use subsystem. The author also lists some indicators for the System.
文摘Differences in knowledge regimes and growth dynamics amongst four ideal types of knowledge based firms are analyzed. Two aspects of technological knowledge, technological opportunity and appropriability are traditionally seen as vital to understand the incentives for research and development activities in firms. However, they do not fully define the technology regimes, when one asks how the knowledge based firm competes. Therefore, the dynamic nature of firm capabilities and knowledge development in terms of expansion and in terms of deepening are also discussed. These two additional aspects of knowledge implies that even if all firms in an industry can be considered to be knowledge intensive these firms do also differ. Using cases of entrepreneurial start-up firms in Sweden, we illustrate whether our conceptual ideas of knowledge development help us understand the diversity and contradictions of firm evolution. Our finding is that firm evolution and capability development is dependent upon both the potential for expanding knowledge, such as by innovations, and by deepening the understanding within established knowledge, such as by learning. This implies that the shaping of a science based industry must be seen in relation both to the value of current knowledge and capabilities together with the sometimes only limited and temporarily advantages of radical innovations.
基金supported by the NationalKeyR&DProgramof China underGrant No.2018YFA0701604.
文摘Due to the many types of distributed denial-of-service attacks(DDoS)attacks and the large amount of data generated,it becomes a chal-lenge to manage and apply the malicious behavior knowledge generated by DDoS attacks.We propose a malicious behavior knowledge base framework for DDoS attacks,which completes the construction and application of a multi-domain malicious behavior knowledge base.First,we collected mali-cious behavior traffic generated by five mainstream DDoS attacks.At the same time,we completed the knowledge collection mechanism through data pre-processing and dataset design.Then,we designed a malicious behavior category graph and malicious behavior structure graph for the characteristic information and spatial structure of DDoS attacks and completed the knowl-edge learning mechanism using a graph neural network model.To protect the data privacy of multiple multi-domain malicious behavior knowledge bases,we implement the knowledge-sharing mechanism based on federated learning.Finally,we store the constructed knowledge graphs,graph neural network model,and Federated model into the malicious behavior knowledge base to complete the knowledge management mechanism.The experimental results show that our proposed system architecture can effectively construct and apply the malicious behavior knowledge base,and the detection capability of multiple DDoS attacks occurring in the network reaches above 0.95,while there exists a certain anti-interference capability for data poisoning cases.
基金supported by National Natural Science Foundation of China(Grant No.51175086)
文摘Due to the insufficiency of utilizing knowledge to guide the complex optimal searching, existing genetic algorithms fail to effectively solve excavator boom structural optimization problem. To improve the optimization efficiency and quality, a new knowledge-based real-coded genetic algorithm is proposed. A dual evolution mechanism combining knowledge evolution with genetic algorithm is established to extract, handle and utilize the shallow and deep implicit constraint knowledge to guide the optimal searching of genetic algorithm circularly. Based on this dual evolution mechanism, knowledge evolution and population evolution can be connected by knowledge influence operators to improve the conflgurability of knowledge and genetic operators. Then, the new knowledge-based selection operator, crossover operator and mutation operator are proposed to integrate the optimal process knowledge and domain culture to guide the excavator boom structural optimization. Eight kinds of testing algorithms, which include different genetic operators, arc taken as examples to solve the structural optimization of a medium-sized excavator boom. By comparing the results of optimization, it is shown that the algorithm including all the new knowledge-based genetic operators can more remarkably improve the evolutionary rate and searching ability than other testing algorithms, which demonstrates the effectiveness of knowledge for guiding optimal searching. The proposed knowledge-based genetic algorithm by combining multi-level knowledge evolution with numerical optimization provides a new effective method for solving the complex engineering optimization problem.
基金Projects(70671039,71071052) supported by the National Natural Science Foundation of ChinaProjects(10QX44,09QX68) supported by the Fundamental Research Funds for the Central Universities in China
文摘Short-term forecasting is a difficult problem because of the influence of non-linear factors and irregular events.A novel short-term forecasting method named TIK was proposed,in which ARMA forecasting model was used to consider the load time series trend forecasting,intelligence forecasting DESVR model was applied to estimate the non-linear influence,and knowledge mining methods were applied to correct the errors caused by irregular events.In order to prove the effectiveness of the proposed model,an application of the daily maximum load forecasting was evaluated.The experimental results show that the DESVR model improves the mean absolute percentage error(MAPE) from 2.82% to 2.55%,and the knowledge rules can improve the MAPE from 2.55% to 2.30%.Compared with the single ARMA forecasting method and ARMA combined SVR forecasting method,it can be proved that TIK method gains the best performance in short-term load forecasting.
基金Supported in part by The Ministry of EducationCulture+1 种基金SportsScience and Technology of Japan under Grant-in-Aid for Scient
文摘Traditional information systems are passive, i.e., data or knowledge is created, retrieved, modified, updated, and deleted only in response to operations issued by users or application programs, and the systems only can execute queries or transactions explicitly submitted by users or application programs but have no ability to do something actively by themselves. Unlike a traditional information system serving just as a storehouse of data or knowledge and working passively according to queries or transactions explicitly issued by users and application programs, an autonomous evolutionary information system serves as an autonomous and evolutionary partner of its users that discovers new knowledge from its database or knowledge base autonomously, cooperates with its users in solving problems actively by providing the users with advices, and has a certain mechanism to improve its own state of “knowing” and ability of “working”. This paper seminally defines what is an autonomous evolutionary information system, explain why autonomous evolutionary information systems are needed, and presents some new issues, fundamental considerations, and research directions in design and development of autonomous evolutionary information systems.
文摘The growth and evolution of domain knowledge have always been the focus of Library and Information Science.Exploring the emergence of correlations in the process of knowledge growth with network science thinking can reveal the growth patterns and mechanisms of knowledge correlations.
文摘气候问题日趋严重,“双碳”目标引起学者的广泛关注。为分析当前国内外“双碳”领域研究前沿与热点差异,本文利用科学计量技术,针对知网和Web of Science核心数据集自2009—2022年有关“双碳”目标的文献进行时空维度内文献分布特征分析和研究前沿与热点动态演化分析。结果表明:“双碳”领域正处于研究浪潮阶段,自2020年后“双碳”领域发文量呈爆发式增长,研究力量集中于西方发达国家。研究侧重点存在差异,国外“双碳”领域从生物质和太阳能利用等技术角度展开研究,国内则侧重政策治理层面,低碳转型成为研究热点。本文提出“双碳”领域未来发展方向将聚焦于低碳技术和模式创新,以创新助推低碳转型。
文摘以中国知网(CNKI)和Web of Science为数据源,以智能建造领域2000—2023年期间的高质量文献为对象,借助CiteSpace对筛选出的中外文献进行分析,探讨智能建造当前的研究热点及其演进趋势。结果表明:研究主题方面,中外文献均围绕信息化展开;研究热点方面,中文文献从研究对象、智能建造技术及研究内容等多种视角开展研究,外文文献重点关注数字化技术在建设项目全生命周期的应用;热点演进趋势方面,中文文献划分为信息化引入、信息化与数智化的初步探索、数字化与绿色智能化的全面应用三个阶段,外文文献可分为技术与理论初探、信息化与自动化、数字化与智能化三个阶段,总体上,中文文献的研究在学习和借鉴外文文献研究的过程中不断深化与成熟,且绿色智能化是未来的研究焦点。
