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城市环境设计 2010年第10期 108-109页

big成立于丹麦的哥本哈根,由一群活动在建筑、城市、研究和开发等领域的建筑师、设计师和思想者组成。在已建成的作品当中,big体现出了功能和技术上的创新性以及在造价和资源利用中

关键词：哥本哈根功能丹麦建筑师美术家思想者 big

Schedulable capacity forecasting for electric vehicles based on big data analysis

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Journal of Modern Power Systems and Clean Energy 2019年第6期7卷 1651-1662页

作者： Meiqin MAO Shengliang ZHANG Liuchen CHANG Nikos D.HATZIARGYRIOU Research Center for Photovoltaic System Engineering School of Electrical Engineering and AutomationHefei University of TechnologyHefei 230009China University of New Brunswick FrederictonNB E3B 5A3Canada National Technical University of Athens 15780 AthensGreece

Fast and accurate forecasting of schedulable capacity of electric vehicles(EVs)plays an important role in enabling the integration of EVs into future smart grids as distributed energy storage *** methods are insufficient to deal with large-scale actual schedulable capacity *** paper proposes forecasting models for schedulable capacity of EVs through the parallel gradient boosting decision tree algorithm and big data analysis for multi-time *** time scale of these data analysis comprises the real time of one minute,ultra-short-term of one hour and one-day-ahead scale of 24 *** predicted results for different time scales can be used for various ancillary *** proposed algorithm is validated using operation data of 521 EVs in the *** results show that compared with other machine learning methods such as the parallel random forest algorithm and parallel k-nearest neighbor algorithm,the proposed algorithm requires less training time with better forecasting accuracy and analytical processing ability in big data environment.

关键词： Electric vehicle(EV) Schedulable capacity Machine learning big data Multi-time scale

big spatial data for urban and environmental sustainability

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Geo-Spatial Information Science 2020年第2期23卷 125-140页

作者： Bo Huang Jionghua Wang Department of Geography and Resource Management The Chinese University of Hong KongHong KongChina

Eighty percent of big data are associated with spatial information,and thus are big Spatial Data(BSD).BSD provides new and great opportunities to rework problems in urban and environmental sustainability with advanced BSD *** fully leverage the advantages of BSD,it is integrated with conventional data(*** sensing images)and improved methods are *** paper introduces four case studies:(1)Detection of polycentric urban structures;(2)Evaluation of urban vibrancy;(3)Estimation of population exposure to PM2.5;and(4)Urban land-use classification via deep *** results provide evidence that integrated methods can harness the advantages of both traditional data and ***,they can also improve the effectiveness of big data ***,this study makes three key recommendations for the development of BSD with regards to data fusion,data and predicting analytics,and theoretical modeling.

关键词： big spatial data analytics review spatial modeling data fusion

big Data Analytics in Healthcare: Data-Driven Methods for Typical Treatment Pattern Mining

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Journal of Systems Science and Systems Engineering 2019年第6期28卷 694-714页

作者： Chonghui Guo Jingfeng Chen Institute of Systems Engineering Dalian University of TechnologyDalian 116024China

A huge volume of digitized clinical data is generated and accumulated rapidly since the widespread adoption of Electronic Medical Records (EMRs).These big data in healthcare hold the promise of propelling healthcare evolving from a proficiency-based art to a data-driven science,from a reactive mode to a proactive mode,from one-size-fits-all medicine to personalized *** paper first discusses the research background-big data analytics in healthcare,the research framework of big data analytics in healthcare,analysis of medical process,and the literature summary of treatment pattern *** the challenges for data-driven typical treatment pattern mining are highlighted,including similarity measure between treatment records,typical treatment pattern extraction,evaluation and recommendation,when considering the rich temporal and heterogeneous medical information in ***,three categories of typical treatment patterns are mined from doctor order content,duration,and sequence view respectively,which can provide a data-driven guideline to achieve the "5R" goal for rational drug use and clinical pathways.

关键词： big data analytics healthcare electronic medical records typical treatment pattern

A review of control loop monitoring and diagnosis:Prospects of controller maintenance in big data era

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Chinese Journal of Chemical Engineering 2016年第8期24卷 952-962页

作者： Xinqing Gao Fan Yang Chao Shang Dexian Huang Department of Automation Tsinghua University Tsinghua National Laboratory for Information Science and Technology

Owing to wide applications of automatic control systems in the process industries, the impacts of controller performance on industrial processes are becoming increasingly significant. Consequently, controller maintenance is critical to guarantee routine operations of industrial processes. The workflow of controller maintenance generally involves the following steps: monitor operating controller performance and detect performance degradation, diagnose probable root causes of control system malfunctions, and take specific actions to resolve associated problems. In this article, a comprehensive overview of the mainstream of control loop monitoring and diagnosis is provided, and some existing problems are also analyzed and discussed. From the viewpoint of synthesizing abundant information in the context of big data, some prospective ideas and promising methods are outlined to potentially solve problems in industrial applications.

关键词： Control loop performance assessment Industrial alarm system Process knowledge Root cause diagnosis big data

big data analytics: six techniques

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Geo-Spatial Information Science 2016年第2期19卷中插3-中插3,119-128页

作者： Hong Shu The State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing (LIESMARS)Wuhan UniversityWuhanChina Collaborative Innovation Center of Geospatial Technology Wuhan UniversityWuhanChina

big data have 4V characteristics of volume, variety, velocity, and veracity, which authentically calls for big data analytics. However, what are the dominant characteristics of big data analysis? Here, the analytics is related to the entire methodology rather than the individual specific analysis. In this paper, six techniques concerning big data analytics are proposed, which include: (1) Ensemble analysis related to a large volume of data, (2) Association analysis related to unknown data sampling, (3) High-dimensional analysis related to a variety of data, (4) Deep analysis related to the veracity of data, (5) Precision analysis related to the veracity of data, and (6) Divide-and-conquer analysis related to the velocity of *** essential of big data analytics is the structural analysis of big data in an optimal criterion of physics, computation, and human cognition. fundamentally, two theoretical challenges, ie the violation of independent and identical distribution, and the extension of general set-theory, are posed. In particular, we have illustrated three kinds of association in geographical big data, ie geometrical associations in space and time, spatiotemporal correlations in statistics, and space-time relations in semantics. furthermore, we have illustrated three kinds of spatiotemporal data analysis, ie measurement (observation) adjustment of geometrical quantities, human spatial behavior analysis with trajectories, data assimilation of physical models and various observations, from which spatiotemporal big data analysis may be largely derived.

关键词： big data ensemble analysis association analysis high-dimensional analysis deep analysis precision analysis divide-and-conquer analysis

Dynamic data auditing scheme for big data storage

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Frontiers of Computer Science 2020年第1期14卷 219-229页

作者： Xingyue CHEN Tao SHANG Feng ZHANG Jianwei LIU Zhenyu GUAN School of Electronic and Information Engineering Beihang UniversityBeijing 100083China School of Cyber Science and Technology Beihang UniversityBeijing 100083China

When users store data in big data platforms,the integrity of outsourced data is a major concern for data owners due to the lack of direct control over the ***,the existing remote data auditing schemes for big data platforms are only applicable to static *** order to verify the integrity of dynamic data in a Hadoop big data platform,we presents a dynamic auditing scheme meeting the special requirement of ***,a new data structure,namely Data Block Index Table,is designed to support dynamic data operations on HDFS(Hadoop distributed file system),including appending,inserting,deleting,and *** combined with the MapReduce framework,a dynamic auditing algorithm is designed to audit the data on HDFS *** shows that the proposed scheme is secure enough to resist forge attack,replace attack and replay attack on big data *** is also efficient in both computation and communication.

关键词： big data data security remote data auditing dynamic update privacy protection

A Classifier Using Online Bagging Ensemble Method for big Data Stream Learning

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Tsinghua Science and Technology 2019年第4期24卷 379-388页

作者： Yanxia Lv Sancheng Peng Ying Yuan Cong Wang Pengfei Yin Jiemin Liu Cuirong Wang School of Computer Science and Engineering Northeastern University Laboratory of Language Engineering and Computing and also with School of Cyber SecurityGuangdong University of Foreign Studies School of Information Science and Engineering Central South University

By combining multiple weak learners with concept drift in the classification of big data stream learning, the ensemble learning can achieve better generalization performance than the single learning approach. In this paper,we present an efficient classifier using the online bagging ensemble method for big data stream learning. In this classifier, we introduce an efficient online resampling mechanism on the training instances, and use a robust coding method based on error-correcting output codes. This is done in order to reduce the effects of correlations between the classifiers and increase the diversity of the ensemble. A dynamic updating model based on classification performance is adopted to reduce the unnecessary updating operations and improve the efficiency of *** implement a parallel version of EoBag, which runs faster than the serial version, and results indicate that the classification performance is almost the same as the serial one. Finally, we compare the performance of classification and the usage of resources with other state-of-the-art algorithms using the artificial and the actual data sets, respectively. Results show that the proposed algorithm can obtain better accuracy and more feasible usage of resources for the classification of big data stream.

关键词： big data stream classification online bagging ensemble learning concept drift

Development and Application of big Data Platform for Garlic Industry Chain

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Computers, Materials & Continua 2019年第1期58卷 229-248页

作者： Weijie Chen Guo Feng Chao Zhang Pingzeng Liu Wanming Ren Ning Cao Jianrui Ding Shandong Agricultural University Tai’an271000China Shandong Provincial Agricultural Information Center Ji’nan250013China College of Information Engineering Qingdao Binhai UniversityQingdao266000China Department of Computer Science Utah State UniversityLoganUSA

In order to effectively solve the problems which affect the stable and healthy development of garlic industry,such as the uncertainty of the planting scale and production data,the influence factors of price fluctuation is difficult to be accurately analyzed,the difficult to predict the trend of price change,the uncertainty of the market concentration,and the difficulty of the short-term price prediction *** big data platform of the garlic industry chain has been *** with a variety of data acquisition technology,the information collection of influencing factors for garlic industry chain is *** on the construction of the big data technology platform,the real-time synchronous acquisition,efficient storage and analysis of the planting,market,storage,processing,export and logistics information in five provinces and seven counties are *** application of the big data platform for garlic industry chain has realized the accurate acquisition of garlic planting area,the price and trend of market circulation and the information of export information,analyzed the fluctuation regulation of garlic price,and also realized the short-term precision prediction of garlic price.

关键词： Garlic industry chain agricultural big data planting area price fluctuation regulation price prediction

Optimal PID Control of Spatial Inverted Pendulum With big Bang–big Crunch Optimization

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IEEE/CAA Journal of Automatica Sinica 2020年第3期7卷 822-832页

作者： Jia-Jun Wang Tufan Kumbasar School of Automation Hangzhou Dianzi UniversityHangzhou 310018China IEEE Control and Automation Engineering Department Faculty of Electrical and Electronics EngineeringIstanbul Technical UniversityIstanbul TR-34469Turkey

As the extension of the linear inverted pendulum(LIP) and planar inverted pendulum(PIP), this paper proposes a novel spatial inverted pendulum(SIP). The SIP is the most general inverted pendulum(IP) than any existing IP. The model of the SIP is presented for the first time. The SIP inherits all the characteristics of the LIP and the PIP, which is a nonlinear,unstable and underactuated system. The SIP has five degrees of motion freedom and three control forces. Thus, it is a multipleinput and multiple-output(MIMO) system with nonlinear dynamics. To realize the spatial trajectory tracking of the SIP,the control structure with five PID controllers will be *** parameter tuning of the multiple PIDs is a challenging work for the proposed SIP model. To alleviate the difficulties of the parameter tuning for the multiple PID controllers, optimal PIDs can be achieved with the help of big Bang – big Crunch(BBBC) optimization. The BBBC algorithm can successfully optimize the parameters of the multiple PID controllers with high convergence speed. The optimization performance index of the BBBC algorithm is compared with that of the particle swarm optimization(PSO). Simulation results certify the rightness and effectiveness of the proposed control and optimization methods.

关键词： big Bang–big Crunch(BBBC) optimal PID control spatial inverted pendulum(SIP) spatial trajectory tracking