Background:Research in various academic disciplines has undergone tremendous changes in the era of big data.Everyone is talking about big data nowadays,but how exactly is it being applied in research on financial stud...Background:Research in various academic disciplines has undergone tremendous changes in the era of big data.Everyone is talking about big data nowadays,but how exactly is it being applied in research on financial studies?Results:This study summarizes the sources of Internet big data for research related to capital markets and the analytical methods that have been used in the literature.In addition,it presents a review of the research findings based on Internet big data in the field of capital markets and proposes suggestions for future studies in which big data can be applied to examine issues related to capital markets.Conclusion:(1)Internet big data sources related to present capital market research can be categorized into forum-type data,microblog-type data and search class data.(2)As for research about investors’sentiments on the basis of Internet big data,the main methods of sentiment analysis include building an inventory of lexical categories,using dictionaries for analysis of lexical categories,and machine learning.(3)Many studies address whether Internet big data can predict capital markets.However,they reach no consistent conclusions,which could be due to limitations of sample and analysis method used.(4)Data collection technique and analysis methods require further improvements.展开更多
Energy Internet is deeply integrated by Internet concept, information technology and energy industry, and Energy Internet Big Data are one of core technologies that achieve energy-information-economic interconnection ...Energy Internet is deeply integrated by Internet concept, information technology and energy industry, and Energy Internet Big Data are one of core technologies that achieve energy-information-economic interconnection and improve the development and evolution of Energy Internet. This paper describes the concept and characteristics of Energy Internet Big Data, and feasibility of applying Energy Internet Big Data to integrated energy market. On this basis, as for integrated energy market and multi-subjects of Energy Internet, typical application and technical system based on Energy Internet Big Data in integrated energy market is put forward, which provides a reference for the analysis and decision of integrated energy market in Energy Internet.展开更多
In the era of big data,stock markets are closely connected with Internet big data from diverse sources.This paper makes the first attempt to compare the linkage between stock markets and various Internet big data coll...In the era of big data,stock markets are closely connected with Internet big data from diverse sources.This paper makes the first attempt to compare the linkage between stock markets and various Internet big data collected from search engines,public media and social media.To achieve this purpose,a big data-based causality testing framework is proposed with three steps,i.e.,data crawling,data mining and causality testing.Taking the Shanghai Stock Exchange and Shenzhen Stock Exchange as targets for stock markets,web search data,news,and microblogs as samples of Internet big data,some interesting findings can be obtained.1)There is a strong bi-directional,linear and nonlinear Granger causality between stock markets and investors'web search behaviors due to some similar trends and uncertain factors.2)News sentiments from public media have Granger causality with stock markets in a bi-directional linear way,while microblog sentiments from social media have Granger causality with stock markets in a unidirectional linear way,running from stock markets to microblog sentiments.3)News sentiments can explain the changes in stock markets better than microblog sentiments due to their authority.The results of this paper might provide some valuable information for both stock market investors and modelers.展开更多
This paper explains the basic concepts of " Internet + " and big data,analyzes the main problems in the application of big data technology in agricultural informationization of Shandong Province,summarizes c...This paper explains the basic concepts of " Internet + " and big data,analyzes the main problems in the application of big data technology in agricultural informationization of Shandong Province,summarizes corresponding solutions from the aspects of government guidance,financial input,open sharing of agricultural big data,big data storage and processing,data mining,etc.,and prospects the application trend of big data technology in agricultural informationization to achieve the connotative development of agriculture in Shandong Province.展开更多
The fast technology development of 5G mobile broadband (5G), Internet of Things (IoT), Big Data Analytics (Big Data), Cloud Computing (Cloud) and Software Defined Networks (SDN) has made those technologies one after a...The fast technology development of 5G mobile broadband (5G), Internet of Things (IoT), Big Data Analytics (Big Data), Cloud Computing (Cloud) and Software Defined Networks (SDN) has made those technologies one after another and created strong interdependence among one another. For example, IoT applications that generate small data with large volume and fast velocity will need 5G with characteristics of high data rate and low latency to transmit such data faster and cheaper. On the other hand, those data also need Cloud to process and to store and furthermore, SDN to provide scalable network infrastructure to transport this large volume of data in an optimal way. This article explores the technical relationships among the development of IoT, Big Data, Cloud, and SDN in the coming 5G era and illustrates several ongoing programs and applications at National Chiao Tung University that are based on the converging of those technologies.展开更多
为了提高钢结构工程质量管理的智能化水平,论文提出了一种基于物联网、大数据分析和人工智能技术的智能监督系统。论文将提出的优化系统工具与现有的两种结构健康监测工具SHMTools(Structural Health Monitoring Tools)和mFUSE(WATLAB F...为了提高钢结构工程质量管理的智能化水平,论文提出了一种基于物联网、大数据分析和人工智能技术的智能监督系统。论文将提出的优化系统工具与现有的两种结构健康监测工具SHMTools(Structural Health Monitoring Tools)和mFUSE(WATLAB Function Sequencer)进行了对比并开展了不同数据量下的实验研究。对比实验结果如下:在预警响应时间方面,优化系统的响应时间从1000数据量的0.65 s提升到3000数据量的0.69 s;在反馈处理效率方面,优化系统从1000数据量的84.20%提升到3000数据量的88.50%,而SHMTools和mFUSE系统分别为75.32%~78.15%和78.65%~81.55%;在系统稳定性方面,优化系统在3000数据量下依然保持96.55%的高稳定性;在资源利用率方面,优化系统从1000数据量的82.45%下降到3000数据量的79.10%。本研究在钢结构工程质量监控智能化方面进行创新探索,为钢结构工程质量和安全管理提供更可靠的技术支持。展开更多
基金National Nature Sciences Foundation of China(No.71372148).
文摘Background:Research in various academic disciplines has undergone tremendous changes in the era of big data.Everyone is talking about big data nowadays,but how exactly is it being applied in research on financial studies?Results:This study summarizes the sources of Internet big data for research related to capital markets and the analytical methods that have been used in the literature.In addition,it presents a review of the research findings based on Internet big data in the field of capital markets and proposes suggestions for future studies in which big data can be applied to examine issues related to capital markets.Conclusion:(1)Internet big data sources related to present capital market research can be categorized into forum-type data,microblog-type data and search class data.(2)As for research about investors’sentiments on the basis of Internet big data,the main methods of sentiment analysis include building an inventory of lexical categories,using dictionaries for analysis of lexical categories,and machine learning.(3)Many studies address whether Internet big data can predict capital markets.However,they reach no consistent conclusions,which could be due to limitations of sample and analysis method used.(4)Data collection technique and analysis methods require further improvements.
文摘Energy Internet is deeply integrated by Internet concept, information technology and energy industry, and Energy Internet Big Data are one of core technologies that achieve energy-information-economic interconnection and improve the development and evolution of Energy Internet. This paper describes the concept and characteristics of Energy Internet Big Data, and feasibility of applying Energy Internet Big Data to integrated energy market. On this basis, as for integrated energy market and multi-subjects of Energy Internet, typical application and technical system based on Energy Internet Big Data in integrated energy market is put forward, which provides a reference for the analysis and decision of integrated energy market in Energy Internet.
基金sponsored by the National Natural Science Foundation of China under Grant Nos.715732447153201371202115 and 71403260。
文摘In the era of big data,stock markets are closely connected with Internet big data from diverse sources.This paper makes the first attempt to compare the linkage between stock markets and various Internet big data collected from search engines,public media and social media.To achieve this purpose,a big data-based causality testing framework is proposed with three steps,i.e.,data crawling,data mining and causality testing.Taking the Shanghai Stock Exchange and Shenzhen Stock Exchange as targets for stock markets,web search data,news,and microblogs as samples of Internet big data,some interesting findings can be obtained.1)There is a strong bi-directional,linear and nonlinear Granger causality between stock markets and investors'web search behaviors due to some similar trends and uncertain factors.2)News sentiments from public media have Granger causality with stock markets in a bi-directional linear way,while microblog sentiments from social media have Granger causality with stock markets in a unidirectional linear way,running from stock markets to microblog sentiments.3)News sentiments can explain the changes in stock markets better than microblog sentiments due to their authority.The results of this paper might provide some valuable information for both stock market investors and modelers.
基金Supported by Science Research Foundation of Binzhou University(BZXYG1712,BZXYG1714)Teaching and Research Project(BZXYSYXM201606,BZXYWTXM201621)Soft Science Research Project of Shandong Province(2018RKB01136)
文摘This paper explains the basic concepts of " Internet + " and big data,analyzes the main problems in the application of big data technology in agricultural informationization of Shandong Province,summarizes corresponding solutions from the aspects of government guidance,financial input,open sharing of agricultural big data,big data storage and processing,data mining,etc.,and prospects the application trend of big data technology in agricultural informationization to achieve the connotative development of agriculture in Shandong Province.
文摘The fast technology development of 5G mobile broadband (5G), Internet of Things (IoT), Big Data Analytics (Big Data), Cloud Computing (Cloud) and Software Defined Networks (SDN) has made those technologies one after another and created strong interdependence among one another. For example, IoT applications that generate small data with large volume and fast velocity will need 5G with characteristics of high data rate and low latency to transmit such data faster and cheaper. On the other hand, those data also need Cloud to process and to store and furthermore, SDN to provide scalable network infrastructure to transport this large volume of data in an optimal way. This article explores the technical relationships among the development of IoT, Big Data, Cloud, and SDN in the coming 5G era and illustrates several ongoing programs and applications at National Chiao Tung University that are based on the converging of those technologies.
文摘为了提高钢结构工程质量管理的智能化水平,论文提出了一种基于物联网、大数据分析和人工智能技术的智能监督系统。论文将提出的优化系统工具与现有的两种结构健康监测工具SHMTools(Structural Health Monitoring Tools)和mFUSE(WATLAB Function Sequencer)进行了对比并开展了不同数据量下的实验研究。对比实验结果如下:在预警响应时间方面,优化系统的响应时间从1000数据量的0.65 s提升到3000数据量的0.69 s;在反馈处理效率方面,优化系统从1000数据量的84.20%提升到3000数据量的88.50%,而SHMTools和mFUSE系统分别为75.32%~78.15%和78.65%~81.55%;在系统稳定性方面,优化系统在3000数据量下依然保持96.55%的高稳定性;在资源利用率方面,优化系统从1000数据量的82.45%下降到3000数据量的79.10%。本研究在钢结构工程质量监控智能化方面进行创新探索,为钢结构工程质量和安全管理提供更可靠的技术支持。
