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| 1 | Identification of Five Stages of Dike Swarms in the Shanxi-Hebei-Inner Mongolia Border Area and Its Tectonic Implications显示文摘Dike swarms are generally ascribed to intrusion of mantle-source magma result from extension. Basic dike swarms around the Shanxi-Hebei-Inner Mogolia borders in the northern peripheral area of the North China Craton can be divided into five age groups according to isotopic dating: 1800-1700 Ma, 800-700 Ma, 230 Ma, 140-120 Ma, and 50-40 Ma. Geological, petrological and isotope geochemical features of the five groups is investigated in order to explore the variation of the mantle material composition in the concerned area with time. And the various extensional activities reflected by the five groups of dike swarms are compared with some important tectonic events within the North China Craton as well as around the world during the same period. | SHAOJi'an ZHAIMingguo ZHANGLüqiao LIDaming | 2004 | Acta Geologica Sinica(English Edition)2004，78，1： | 9 |
| 2 | Suggestion of a dynamic model of North China basin-range system显示文摘It is found from preliminary studies that previous basin-range models have difficulties in explaining the formation of the Mesozoic North-China basin-range system. This work suggests a new model-'tectonic thermal erosion' model, which considers the North China basin of Late Mesozoic and its peripheral ranges as a unified system, identifies relationship between upwelling and lateral spreading of the asthenolith with horizontal movement and deformation of the upper crust in the system, clarifies the effects of underplating erosion on the crustal evolution, and tries to establish an earth-dynamic model of the North China Mesozoic basin-range supported by numerical simulation. | SHAOJi'an ZHANGChanghou ZHANGLüqiao ZHANGYongbei | 2003 | Progress in Natural Science:Materials International2003，13，4： | 6 |
| 3 | Friendship prediction model based on factor graphs integrating geographical location显示文摘With the development of network services and location-based systems,many mobile applications begin to use users’geographical location to provide better services.In terms of social networks,geographical location is actively shared by users.In some applications with recommendation services,before the geographical location recommendation is provided,the authors have to obtain user’s permission.This kind of social network integrated with geographical location information is called location-based social networks(abbreviate for LBSNs).In the LBSN,each user has location information when he or she checked in hotels or feature spots.Based on this information,they can identify user’s trajectory of movement behaviour and activity patterns.In general,if there is friendship between two users,their trajectories in reality are likely to be similar.In this study,according to user’s geographical location information over a period of time,they explore whether there exists friendly relationship between two users based on trajectory similarity and the structure theory of graphs.In particular,they propose a new factor function and a factor graph model based on user’s geographical location to predict the friendship between two users in the real LBSN. | Liang Chen Shaojie Qiao Nan Han Chang-an Yuan Xuejiang Song Ping Huang Yueqiang Xiao | 2020 | CAAI Transactions on Intelligence Technology2020，5，3： | 3 |
| 4 | VCCM mining:Mining virtual community core members based on gene expression programming显示文摘 | Qiao Shaojie Tang Changjie Peng Jing | 2006 | LNCS2006，39，17： | 1 |
| 5 | Survey on vehicle map matching techniques显示文摘With the development of location‐based services and Big data technology,vehicle map matching techniques are growing rapidly,which is the fundamental techniques in the study of exploring global positioning system(GPS)data.The pre‐processed GPS data can provide the guarantee of high‐quality data for the research of mining passenger’s points of interest and urban computing services.The existing surveys mainly focus on map‐matching algorithms,but there are few descriptions on the key phases of the acquisition of sampling data,floating car and road data preprocessing in vehicle map matching systems.To address these limitations,the contribution of this survey on map matching techniques lies in the following aspects:(i)the background knowledge,function and system framework of vehicle map matching techniques;(ii)description of floating car data and road network structure to understand the detailed phase of map matching;(iii)data preprocessing rules,specific methodologies,and significance of floating car and road data;(iv)map matching algorithms are classified by the sampling frequency and data information.The authors give the introduction of open‐source GPS sampling data sets,and the evaluation measurements of map‐matching approaches;(v)the suggestions on data preprocessing and map matching algorithms in the future work. | Zhenfeng Huang Shaojie Qiao Nan Han Chang-an Yuan Xuejiang Song Yueqiang Xiao | 2021 | CAAI Transactions on Intelligence Technology2021，6，1： | 1 |
| 6 | A rough set based dynamic maintenance approach for approximations in coarsening and refining attribute values显示文摘 | Chen Hongrnei Li Tianrui Qiao Shaojie | 2010 | InternationalJournal of Intelligent Systems2010，25，10： | 1 |
| 7 | A Rough Set-based Dynamic Maintenance Approach for Approximations in Coarsening and Refining Attribute Valves显示文摘 | Chen Hongmei Li Tianrui Qiao Shaojie | 2010 | International Journal of Intelligent System2010，25，10： | 1 |
| 8 | PutMode: prediction of uncertain trajectories in moving objects databases显示文摘 | Shaojie Qiao Changjie Tang Huidong Jin Teng Long Shucheng Dai Yungchang Ku Michael Chau | 2010 | Applied Intelligence2010，，3： | 1 |
| 9 | The fitness evaluation strategy in particle swarm optimization 显示文摘 | Hu Jian Wang Zhiqiang Qiao Shaojie | 2011 | Applied Mathematics and Computation2011，21，： | 1 |
| 10 | Key techniques for predicting the uncertain trajectories of moving objects with dynamic environment awareness显示文摘Emerging technologies of wireless and mobile communication enable people to accumulate a large volume of time-stamped locations,which appear in the form of a continuous moving object trajectory.How to accurately predict the uncertain mobility of objects becomes an important and challenging problem.Existing algorithms for trajectory prediction in moving objects databases mainly focus on identifying frequent trajectory patterns,and do not take account of the effect of essential dynamic environmental factors.In this study,a general schema for predicting uncertain trajectories of moving objects with dynamic environment awareness is presented,and the key techniques in trajectory prediction arc addressed in detail.In order to accurately predict the trajectories,a trajectory prediction algorithm based on continuous time Bayesian networks(CTBNs) is improved and applied,which takes dynamic environmental factors into full consideration.Experiments conducted on synthetic trajectory data verify the effectiveness of the improved algorithm,which also guarantees the time performance as well. | Shaojie QIAO Xian WANG Lu'an TANG Liangxu LIU Xun GONG | 2011 | Journal of Modern Transportation2011，19，3： | 1 |
| 11 | Cooperation Oriented Computing:A Computing Model Based on Emergent Dynamics of Group Cooperation显示文摘Traditional way of problem solving tries to deliver data to program.But when the problem’s complexity exponentially increases as the data scale increases,to obtain the solution is difficult.Group cooperation computing model works in an inverse way by delivering program to data.It first models each single data as individual and data unit as group of individuals.Then,different cooperation rules are designed for individuals to cooperate with each other.Finally,the solution of the problem emerges through individuals’cooperation process.This study applies group cooperation computing model to solve Hamilton Path problem which has NP-complete time complexity.Experiment results show that the cooperation model works much better than genetic algorithm.More importantly,the following properties of group cooperation computing are found which may be different from the traditional computing theory.(1)By using different cooperation rules,the same problem with the same scale may exhibit different complexities,such as liner or exponent.(2)By using the same cooperation rule,when the problem scale is less than a specific threshold,the problem’s time complexity is liner.Otherwise,the problem complexity may be exponent. | Jiaoling Zheng Hongpin Shu Yuanping Xu Shaojie Qiao Liyu Wen | 2015 | 国际计算机前沿大会会议论文集2015，，B12： | 0 |
| 12 | A BiLSTM cardinality estimator in complex database systems based on attention mechanism显示文摘An excellent cardinality estimation can make the query optimiser produce a good execution plan.Although there are some studies on cardinality estimation,the prediction results of existing cardinality estimators are inaccurate and the query efficiency cannot be guaranteed as well.In particular,they are difficult to accurately obtain the complex relationships between multiple tables in complex database systems.When dealing with complex queries,the existing cardinality estimators cannot achieve good results.In this study,a novel cardinality estimator is proposed.It uses the core techniques with the BiLSTM network structure and adds the attention mechanism.First,the columns involved in the query statements in the training set are sampled and compressed into bitmaps.Then,the Word2vec model is used to embed the word vectors about the query statements.Finally,the BiLSTM network and attention mechanism are employed to deal with word vectors.The proposed model takes into consideration not only the correlation between tables but also the processing of complex predicates.Extensive experiments and the evaluation of BiLSTM-Attention Cardinality Estimator(BACE)on the IMDB datasets are conducted.The results show that the deep learning model can significantly improve the quality of cardinality estimation,which is a vital role in query optimisation for complex databases. | Qiang Zhou Guoping Yang Haiquan Song Jin Guo Yadong Zhang Shengjie Wei Lulu Qu Louis Alberto Gutierrez Shaojie Qiao | 2022 | CAAI Transactions on Intelligence Technology2022，7，3： | 0 |
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