|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | Spatial cloud computing: how can the geospatial sciences use and help shape cloud computing?显示文摘The geospatial sciences face grand information technology(IT)challenges in the twenty-first century:data intensity,computing intensity,concurrent access intensity and spatiotemporal intensity.These challenges require the readiness of a computing infrastructure that can:(1)better support discovery,access and utilization of data and data processing so as to relieve scientists and engineers of IT tasks and focus on scientific discoveries;(2)provide real-time IT resources to enable real-time applications,such as emergency response;(3)deal with access spikes;and(4)provide more reliable and scalable service for massive numbers of concurrent users to advance public knowledge.The emergence of cloud computing provides a potential solution with an elastic,on-demand computing platform to integrateobservation systems,parameter extracting algorithms,phenomena simulations,analytical visualization and decision support,and to provide social impact and user feedbackthe essential elements of the geospatial sciences.We discuss the utilization of cloud computing to support the intensities of geospatial sciences by reporting from our investigations on how cloud computing could enable the geospatial sciences and how spatiotemporal principles,the kernel of the geospatial sciences,could be utilized to ensure the benefits of cloud computing.Four research examples are presented to analyze how to:(1)search,access and utilize geospatial data;(2)configure computing infrastructure to enable the computability of intensive simulation models;(3)disseminate and utilize research results for massive numbers of concurrent users;and(4)adopt spatiotemporal principles to support spatiotemporal intensive applications.The paper concludes with a discussion of opportunities and challenges for spatial cloud computing(SCC). | Chaowei Yang Michael Goodchild Qunying Huang Doug Nebert Robert Raskin Yan Xu Myra Bambacus Daniel Fay | 2011 | International Journal of Digital Earth2011，4，4： | 55 |
| 2 | Three-dimensional chiral microstructures fabricated by structured optical vortices in isotropic material显示文摘Optical vortices,a type of structured beam with helical phase wavefronts and‘doughnut’-shaped intensity distributions,have been used to fabricate chiral structures in metals and spiral patterns in anisotropic polarization-dependent azobenzene polymers.However,in isotropic polymers,the fabricated microstructures are typically confined to non-chiral cylindrical geometry due to the two-dimensional‘doughnut’-shaped intensity profile of the optical vortices.Here we develop a powerful strategy to realize chiral microstructures in isotropic material by coaxial interference of a vortex beam and a plane wave,which produces threedimensional(3D)spiral optical fields.These coaxial interference beams are generated by designing contrivable holograms consisting of an azimuthal phase and an equiphase loaded on a liquid-crystal spatial light modulator.In isotropic polymers,3D chiral microstructures are achieved under illumination using coaxial interference femtosecond laser beams with their chirality controlled by the topological charge.Our further investigation reveals that the spiral lobes and chirality are caused by interfering patterns and helical phase wavefronts,respectively.This technique is simple,stable and easy to perform,and it offers broad applications in optical tweezers,optical communications and fast metamaterial fabrication. | Jincheng Ni Chaowei Wang Chenchu Zhang Yanlei Hu Liang Yang Zhaoxin Lao Bing Xu Jiawen Li Dong Wu Jiaru Chu | 2017 | Light(Science & Applications)2017，6，1： | 28 |
| 3 | 无源非线性延迟锁定保护电路的分析显示文摘本文提出一种简单的无源非线性延迟锁定保护电路。它除具有由复杂的数字逻辑电路构成的计数式延迟锁定保护电路的功能外,对实际工程上常用的rc低通电路相关处理情况,还优于后者。本文分析了无源非线性延迟锁定保护电路的性能,给出了理想积分和rc低通电路相关处理两种情况下的锁定保持时间的均值和方差。 | Yang Shizhong Wu Yongxiang Tang Chaowei Fei Huaipu(Chongqing University,Chongqing 630044) | 1996 | 电子学报1996，24，4： | 10 |
| 4 | A hierarchical indexing strategy for optimizing Apache Spark with HDFS to efficiently query big geospatial raster data显示文摘Earth observations and model simulations are generating big multidimensional array-based raster data.However,it is difficult to efficiently query these big raster data due to the inconsistency among the geospatial raster data model,distributed physical data storage model,and the data pipeline in distributed computing frameworks.To efficiently process big geospatial data,this paper proposes a three-layer hierarchical indexing strategy to optimize Apache Spark with Hadoop Distributed File System(HDFS)from the following aspects:(1)improve I/O efficiency by adopting the chunking data structure;(2)keep the workload balance and high data locality by building the global index(k-d tree);(3)enable Spark and HDFS to natively support geospatial raster data formats(e.g.,HDF4,NetCDF4,GeoTiff)by building the local index(hash table);(4)index the in-memory data to further improve geospatial data queries;(5)develop a data repartition strategy to tune the query parallelism while keeping high data locality.The above strategies are implemented by developing the customized RDDs,and evaluated by comparing the performance with that of Spark SQL and SciSpark.The proposed indexing strategy can be applied to other distributed frameworks or cloud-based computing systems to natively support big geospatial data query with high efficiency. | Fei Hu Chaowei Yang Yongyao Jiang Yun Li Weiwei Song Daniel Q.Duffy John L.Schnase Tsengdar Lee | 2020 | International Journal of Digital Earth2020，13，3： | 4 |
| 5 | Crystalline behaviors and phase transition during the manufacture of fine denier PA6 fibers显示文摘Recently we have successfully produced fine denier PA6 fibers by using additives containing lanthanide compounds.Meanwhile,crystallization and phase transition of PA6 fibers during spinning and drawing processes were investigated.During the spinning process,β phase crystal could be obtained in as-spun PA6 fibers which were produced with relatively high melt draw ratio,while γ phase crystal predominated when the melt draw ratio was relatively low.β phase crystal,whose behaviors are similar with those of γ phase by FT-IR and XRD characterization,could be transformed to α form easily when PA6 fibers are immersed in boiling water.However,γ phase crystal of PA6 remains unchanged in boiling water.Thus,β and γ phase crystals of PA6 can be differentiated by the crystalline behaviors of PA6 fibers after treatment in boiling water.Further experiments demonstrate that the β phase can also be produced during a drawing process where a phase transformation from γ to α occurs.In other words,β phase may act as an intermediate state during the phase transformation. | ZHANG ChengFeng LIU YuHai LIU ShaoXuan LI HuiZhen HUANG Kun PAN QingHua HUA XiaoHui HAO ChaoWei MA QingFang LV ChangYou LI WeiHong YANG ZhanLan ZHAO Ying WANG DuJin LAI GuoQiao JIANG JianXiong XU YiZhuang WU JinGuang | 2009 | Science China Chemistry2009，52，11： | 4 |
| 6 | Distributed geospatial information processing: sharing distributed geospatial resources to support Digital Earth显示文摘This paper introduces a new concept,distributed geospatial information processing(DGIP),which refers to the process of geospatial information residing on computers geographically dispersed and connected through computer networks,and the contribution of DGIP to Digital Earth(DE).The DGIP plays a critical role in integrating the widely distributed geospatial resources to support the DE envisioned to utilise a wide variety of information.This paper addresses this role from three different aspects:1)sharing Earth data,information,and services through geospatial interoperability supported by standardisation of contents and interfaces;2)sharing computing and software resources through a GeoCyberinfrastructure supported by DGIP middleware;and 3)sharing knowledge within and across domains through ontology and semantic searches.Observing the long-term process for the research and development of an operational DE,we discuss and expect some practical contributions of the DGIP to the DE. | Chaowei Yang Wenwen Li Jibo Xie Bin Zhou | 2008 | International Journal of Digital Earth2008，1，3： | 4 |
| 7 | Big Data and cloud computing:innovation opportunities and challenges显示文摘Big Data has emerged in the past few years as a new paradigm providing abundant data and opportunities to improve and/or enable research and decision-support applications with unprecedented value for digital earth applications including business,sciences and engineering.At the same time,Big Data presents challenges for digital earth to store,transport,process,mine and serve the data.Cloud computing provides fundamental support to address the challenges with shared computing resources including computing,storage,networking and analytical software;the application of these resources has fostered impressive Big Data advancements.This paper surveys the two frontiers–Big Data and cloud computing–and reviews the advantages and consequences of utilizing cloud computing to tackling Big Data in the digital earth and relevant science domains.From the aspects of a general introduction,sources,challenges,technology status and research opportunities,the following observations are offered:(i)cloud computing and Big Data enable science discoveries and application developments;(ii)cloud computing provides major solutions for Big Data;(iii)Big Data,spatiotemporal thinking and various application domains drive the advancement of cloud computing and relevant technologies with new requirements;(iv)intrinsic spatiotemporal principles of Big Data and geospatial sciences provide the source for finding technical and theoretical solutions to optimize cloud computing and processing Big Data;(v)open availability of Big Data and processing capability pose social challenges of geospatial significance and(vi)a weave of innovations is transforming Big Data into geospatial research,engineering and business values.This review introduces future innovations and a research agenda for cloud computing supporting the transformation of the volume,velocity,variety and veracity into values of Big Data for local to global digital earth science and applications. | Chaowei Yang Qunying Huang Zhenlong Li Kai Liu Fei Hu | 2017 | International Journal of Digital Earth2017，10，1： | 4 |
| 8 | PRECISE ASYMPTOTICS IN SELF-NORMALIZED SUMS OF ITERATED LOGARITHM FOR MULTIDIMENSIONALLY INDEXED RANDOM VARIABLES显示文摘在 Z + d 的情况中(d 鈮 ? 2 ) 积极 d 维的格子与部分订指鈮?{ X k, k 鈭 ? Z + d } 有平均数 0 的 i.i.d 随机变量, S n = 鈭 ? k 鈮 X k 和 V n 2 = 鈭 ? j 鈮 X j 2,精确 asymptotics 为并且,?鈫 ? 0,被建立。 | Jiang Chaowei Yang Xiaorong | 2007 | Applied Mathematics(A Journal of Chinese Universities)2007，22，1： | 3 |
| 9 | Big Earth data analytics:a survey显示文摘Big Earth data are produced from satellite observations,Internet-ofThings,model simulations,and other sources.The data embed unprecedented insights and spatiotemporal stamps of relevant Earth phenomena for improving our understanding,responding,and addressing challenges of Earth sciences and applications.In the past years,new technologies(such as cloud computing,big data and artificial intelligence)have gained momentum in addressing the challenges of using big Earth data for scientific studies and geospatial applications historically intractable.This paper reviews the big Earth data analytics from several aspects to capture the latest advancements in this fast-growing domain.We first introduce the concepts of big Earth data.The architecture,various functionalities,and supporting modules are then reviewed from a generic methodology aspect.Analytical methods supporting the functionalities are surveyed and analyzed in the context of different tools.The driven questions are exemplified through cutting-edge Earth science researches and applications.A list of challenges and opportunities are proposed for different stakeholders to collaboratively advance big Earth data analytics in the near future. | Chaowei Yang Manzhu Yu Yun Li Fei Hu Yongyao Jiang Qian Liu Dexuan Sha Mengchao Xu Juan Gu | 2019 | Big Earth Data2019，3，2： | 3 |
| 10 | Engineering self-healing adhesive hydrogels with antioxidant properties for intrauterine adhesion prevention显示文摘Intrauterine adhesion (IUA) is the fibrosis within the uterine cavity. It is the second most common cause of female infertility, significantly affecting women’s physical and mental health. Current treatment strategies fail to provide a satisfactory therapeutic outcome for IUA patients, leaving an enormous challenge for reproductive science. A self-healing adhesive hydrogel with antioxidant properties will be highly helpful in IUA prevention. In this work, we prepare a series of self-healing hydrogels (P10G15, P10G20, and P10G25) with antioxidant and adhesive properties. Those hydrogels exhibit good self-healing properties and can adapt themselves to different structures. They possess good injectability and fit the shape of the human uterus. Moreover, the hydrogels exhibit good tissue adhesiveness, which is desirable for stable retention and therapeutic efficacy. The in vitro experiments using P10G20 show that the adhesive effectively scavenges ABTS+, DPPH, and hydroxyl radicals, rescuing cells from oxidative stress. In addition, P10G20 offers good hemocompatibility and in vitro and in vivo biocompatibility. Furthermore, P10G20 lowers down the in vivo oxidative stress and prevents IUA with less fibrotic tissue and better endometrial regeneration in the animal model. It can effectively downregulate fibrosis-related transforming growth factor beta 1 (TGF-β1) and vascular endothelial growth factor (VEGF). Altogether, these adhesives may be a good alternative for the clinical treatment of intrauterine adhesion. | Luyao Feng Liqun Wang Yao Ma Wanglin Duan Sergio Martin-Saldana Ye Zhu Xianpeng Zhang Bin Zhu Chaowei Li Shibo Hu Mingjie Bao Ting Wang Yuan Zhu Fei Yang Yazhong Bu | 2023 | Bioactive Materials2023，，9： | 3 |
| 11 | Surfactant-Encapsulated Polyoxometalate Complex as a Cathode Interlayer for Nonfullerene Polymer Solar Cells显示文摘An alcohol-soluble,environmentally friendly,and low-cost surfactant-encapsulated polyoxometalate complex[(C8H17)4N]4[SiW_(12)O40](TOASiW_(12))as a cathode interlayer(CIL)has exhibited excellent universality for various active layers and cathodes in nonfullerene polymer solar cells(NF-PSCs).In particular,incorporating TOASiW_(12) as the CIL enhanced power conversion efficiencies(PCEs)of the PM6:Y6-based NF-PSCs with Al or Ag cathode to 16.14%and 15.89%,respectively,and the PCEs of PM6:BTP-BO4Cl-based NF-PSCs with Al or Ag cathode to 17.04%and 17.00%,respectively.More importantly,the performances of the devices with TOASiW_(12) were insensitive to the TOASiW_(12) thickness from 3 to 33 nm.Furthermore,the NF-PSCs with TOASiW_(12) exhibited better device stability.Combined characterization of the photocurrent density versus effective voltage,capacitance versus voltage and electron mobility demonstrated that TOASiW_(12) as the CIL effectively promoted exciton dissociation,charge-carrier extraction,built-in potential,charge-carrier density,and electron mobility in the NF-PSCs.These findings suggest that TOASiW_(12) is a promising,competitive CIL for NF-PSCs fabricated by roll-to-roll processing. | Jing Qiu Yue Zhang Yan Liu Huiru Liu Dongdong Xia Fan Yang Chaowei Zhao Weiwei Li Lixin Wu Fenghong Li | 2022 | CCS Chemistry2022，4，3： | 3 |
| 12 | Mach-Zehnder Interferometer for High Temperature(1000℃)Sensing Based on a Few-Mode Fiber显示文摘A Mach-Zehnder interferometer(MZI)for high temperature(1000°C)sensing based on few mode fiber(FMF)was proposed and experimentally demonstrated.The sensor was fabricated by fusing a section of FMF between two single-mode fibers(SMFs).The structure was proven to be an excellent high temperature sensor with good stability,repeatability,and high temperature sensitivity(48.2 pm/C)after annealing process at a high temperature lasting some hours,and a wide working temperature range(from room temperature to 1000 C).In addition,the simple fabrication process and the low cost offered a great potential for sensing in high temperature environments. | Juan Liu Chaowei Luo Hua Yang Zhen Yi Bin Liu Xingdao He Qiang Wu | 2021 | Photonic Sensors2021，11，3： | 2 |
| 13 | Spatiotemporal event detection: a review显示文摘The advancements of sensing technologies,including remote sensing,in situ sensing,social sensing,and health sensing,have tremendously improved our capability to observe and record natural and social phenomena,such as natural disasters,presidential elections,and infectious diseases.The observations have provided an unprecedented opportunity to better understand and respond to the spatiotemporal dynamics of the environment,urban settings,health and disease propagation,business decisions,and crisis and crime.Spatiotemporal event detection serves as a gateway to enable a better understanding by detecting events that represent the abnormal status of relevant phenomena.This paper reviews the literature for different sensing capabilities,spatiotemporal event extraction methods,and categories of applications for the detected events.The novelty of this review is to revisit the definition and requirements of event detection and to layout the overall workflow(from sensing and event extraction methods to the operations and decision-supporting processes based on the extracted events)as an agenda for future event detection research.Guidance is presented on the current challenges to this research agenda,and future directions are discussed for conducting spatiotemporal event detection in the era of big data,advanced sensing,and artificial intelligence. | Manzhu Yu Myra Bambacus Guido Cervone Keith Clarke Daniel Duffy Qunying Huang Jing Li Wenwen Li Zhenlong Li Qian Liu Bernd Resch Jingchao Yang Chaowei Yang | 2020 | International Journal of Digital Earth2020，13，12： | 2 |
| 14 | Cryo-EM structure of the hyperpolarization-activated inwardly rectifying potassium channel KAT1 from Arabidopsis显示文摘Dear Editor,Plants utilize K^+ions to maintain hydrostatic pressure,drive irreversible cell expansion for growth,and facilitate reversible changes in guard cell volume that cause stomatal opening or closing.KAT1 is a voltage-dependent potassium channel from Arabidopsis thaliana that is mainly expressed in guard cells.KAT1 allows the influx of K+,leading to the swelling and opening of the stoma,and therefore plays a key role in regulating the aperture of stomatal pores on the surface of plant leaves. | Siyu Li Fan Yang Demeng Sun Yong Zhang Mengge Zhang Sanling Liu Peng Zhou Chaowei Shi Longhua Zhang Changlin Tian | 2020 | Cell Research2020，30，11： | 2 |
| 15 | A spatiotemporal data collection of viral cases for COVID-19 rapid response显示文摘Under the global health crisis of COVID-19,timely,and accurate epi-demic data are important for observation,monitoring,analyzing,modeling,predicting,and mitigating impacts.Viral case data can be jointly analyzed with relevant factors for various applications in the context of the pandemic.Current COVID-19 case data are scattered across a variety of data sources which may consist of low data quality accompanied by inconsistent data structures.To address this short-coming,a multi-scale spatiotemporal data product is proposed as a public repository platform,based on a spatiotemporal cube,and allows the integration of different data sources by adopting various data standards.Within the spatiotemporal cube,a comprehensive data processing workflow gathers disparate COVID-19 epidemic data-sets at the global,national,provincial/state,county,and city levels.This proposed framework is supported by an automatic update with a 2-h frequency and the crowdsourcing validation team to produce and update data on a daily time step.This rapid-response dataset allows the integration of other relevant socio-economic and environ-mental factors for spatiotemporal analysis.The data is available in Harvard Dataverse platform(http://gffzz9c54d31c51204187skxpwoxpqf0qv6owv.ffgz.tsg.suse.edu.cn/dataset.xhtml?persistentId=doi:10.7910/DVN/8HGECN)and GitHub open source repository(http://gffzz188fe103f8f1460askxpwoxpqf0qv6owv.ffgz.tsg.suse.edu.cn/stccenter/COVID-19-Data). | Dexuan Sha Yi Liu Qian Liu Yun Li Yifei Tian Fayez Beaini Cheng Zhong Tao Hu Zifu Wang Hai Lan You Zhou Zhiran Zhang Chaowei Yang | 2021 | Big Earth Data2021，5，1： | 2 |
| 16 | Taking the pulse of COVID-19:a spatiotemporal perspective显示文摘The sudden outbreak of the Coronavirus disease(COVID-19)swept across the world in early 2020,triggering the lockdowns of several billion people across many countries,including China,Spain,India,the U.K.,Italy,France,Germany,Brazil,Russia,and the U.S.The transmission of the virus accelerated rapidly with the most confirmed cases in the U.S.,India,Russia,and Brazil.In response to this national and global emergency,the NSF Spatiotemporal Innovation Center brought together a taskforce of international researchers and assembled implementation strategies to rapidly respond to this crisis,for supporting research,saving lives,and protecting the health of global citizens.This perspective paper presents our collective view on the global health emergency and our effort in collecting,analyzing,and sharing relevant data on global policy and government responses,human mobility,environmental impact,socioeconomical impact;in developing research capabilities and mitigation measures with global scientists,promoting collaborative research on outbreak dynamics,and reflecting on the dynamic responses from human societies. | Chaowei Yang Dexuan Sha Qian Liu Yun Li Hai Lan Weihe Wendy Guan Tao Hu Zhenlong Li Zhiran Zhang John Hoot Thompson Zifu Wang David Wong Shiyang Ruan Manzhu Yu Douglas Richardson Luyao Zhang Ruizhi Hou You Zhoua Cheng Zhong Yifei Tian Fayez Beaini Kyla Carte Colin Flynn Wei Liu Dieter Pfoser Shuming Bao Mei Li Haoyuan Zhang Chunbo Liu Jie Jiang Shihong Du Liang Zhao Mingyue Lu Lin Li Huan Zhou Andrew Ding | 2020 | International Journal of Digital Earth2020，13，10： | 2 |
| 17 | Redefining the possibility of digital Earth and geosciences with spatial cloud computing显示文摘Global challenges(such as economy and natural hazards)and technology advancements have triggered international leaders and organizations to rethink geosciences and Digital Earth in the new decade.The next generation visions pose grand challenges for infrastructure,especially computing infrastructure.The gradual establishment of cloud computing as a primary infrastructure provides new capabilities to meet the challenges.This paper reviews research conducted using cloud computing to address geoscience and Digital Earth needs within the context of an integrated Earth system.We also introduce the five papers selected through a rigorous review process as exemplar research in using cloud capabilities to address the challenges.The literature and research demonstrate that spatial cloud computing provides unprecedented new capabilities to enable Digital Earth and geosciences in the twenty-first century in several aspects:(1)virtually unlimited computing power for addressing big data storage,sharing,processing,and knowledge discovering challenges,(2)elastic,flexible,and easy-to-use computing infrastructure to facilitate the building of the next generation geospatial cyberin-frastructure,CyberGIS,CloudGIS,and Digital Earth,(3)seamless integration environment that enables mashing up observation,data,models,problems,and citizens,(4)research opportunities triggered by global challenges that may lead to breakthroughs in relevant fields including infrastructure building,GIScience,computer science,and geosciences,and(5)collaboration supported by cloud computing and across science domains,agencies,countries to collectively address global challenges from policy,management,system engineering,acquisition,and operation aspects. | Chaowei Yang Yan Xu Douglas Nebert | 2013 | International Journal of Digital Earth2013，6，4： | 2 |
| 18 | Utilize cloud computing to support dust storm forecasting显示文摘The simulations and potential forecasting of dust storms are of significant interest to public health and environment sciences.Dust storms have interannual variabilities and are typical disruptive events.The computing platform for a dust storm forecasting operational system should support a disruptive fashion by scaling up to enable high-resolution forecasting and massive public access when dust storms come and scaling down when no dust storm events occur to save energy and costs.With the capability of providing a large,elastic,and virtualized pool of computational resources,cloud computing becomes a new and advantageous computing paradigm to resolve scientific problems traditionally requiring a large-scale and high-performance cluster.This paper examines the viability for cloud computing to support dust storm forecasting.Through a holistic study by systematically comparing cloud computing using Amazon EC2 to traditional high performance computing(HPC)cluster,we find that cloud computing is emerging as a credible solution for(1)supporting dust storm forecasting in spinning off a large group of computing resources in a few minutes to satisfy the disruptive computing requirements of dust storm forecasting,(2)performing high-resolution dust storm forecasting when required,(3)supporting concurrent computing requirements,(4)supporting real dust storm event forecasting for a large geographic domain by using recent dust storm event in Phoniex,05 July 2011 as example,and(5)reducing cost by maintaining low computing support when there is no dust storm events while invoking a large amount of computing resource to perform high-resolution forecasting and responding to large amount of concurrent public accesses. | Qunying Huang Chaowei Yang Karl Benedict Songqing Chen Abdelmounaam Rezgui Jibo Xie | 2013 | International Journal of Digital Earth2013，6，4： | 2 |
| 19 | Per- formance-improving techniques in web-based GIS显示文摘 | YANG Chaowei WONG D W YANG Ruixin | 2005 | Inter- national Journal of Geographical Information Science2005，19，3： | 1 |
| 20 | Deep learning for real-time social media text classification for situation awareness-using Hurricanes Sandy,Harvey,and Irma as case studies显示文摘Social media platforms have been contributing to disaster management during the past several years.Text mining solutions using traditional machine learning techniques have been developed to categorize the messages into different themes,such as caution and advice,to better understand the meaning and leverage useful information from the social media text content.However,these methods are mostly event specific and difficult to generalize for cross-event classifications.In other words,traditional classification models trained by historic datasets are not capable of categorizing social media messages from a future event.This research examines the capability of a convolutional neural network(CNN)model in cross-event Twitter topic classification based on three geo-tagged twitter datasets collected during Hurricanes Sandy,Harvey,and Irma.The performance of the CNN model is compared to two traditional machine learning methods:support vector machine(SVM)and logistic regression(LR).Experiment results showed that CNN models achieved a consistently better accuracy for both single event and crossevent evaluation scenarios whereas SVM and LR models had lower accuracy compared to their own single event accuracy results.This indicated that the CNN model has the capability of pre-training Twitter data from past events to classify for an upcoming event for situational awareness. | Manzhu Yu Qunying Huang Han Qin Chris Scheele Chaowei Yang | 2019 | International Journal of Digital Earth2019，12，11： | 1 |
您所在的机构暂未开通此部分的功能，请联系管理员