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Friendship prediction model based on factor graphs integrating geographical location

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CAAI Transactions on Intelligence Technology 2020年第3期5卷 193-199页

作者： Liang Chen shaojie qiao Nan Han Chang-an Yuan Xuejiang Song Ping Huang Yueqiang Xiao School of Software Engineering Chengdu University of Information TechnologyChengdu 610225People’s Republic of China School of Management Chengdu University of Information TechnologyChengdu 610103People’s Republic of China School of Computer and Information Engineering Nanning Normal UniversityNanning Guangxi 530299People’s Republic of China Guangxi College of Education Nanning Guangxi 530023People’s Republic of China Chengdu Tanmer Technology Co. LtdChengdu 610000People’s Republic of China

With the development of network services and location-based systems,many mobile applications begin to use users’geographical location to provide better *** terms of social networks,geographical location is actively shared by *** some applications with recommendation services,before the geographical location recommendation is provided,the authors have to obtain user’s *** 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 *** on this information,they can identify user’s trajectory of movement behaviour and activity *** general,if there is friendship between two users,their trajectories in reality are likely to be *** 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 *** 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.

关键词： LBS services prediction

A BiLSTM cardinality estimator in complex database systems based on attention mechanism

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CAAI Transactions on Intelligence Technology 2022年第3期7卷 537-546页

作者： Qiang Zhou Guoping Yang Haiquan Song Jin Guo Yadong Zhang Shengjie Wei Lulu Qu Louis Alberto Gutierrez shaojie qiao School of Information Science and Technology Southwest Jiaotong UniversityChengduChina School of Software Engineering Chengdu University of Information TechnologyChengduChina School of Energy Power and Mechanical Engineering North China Electric Power UniversityBaodingChina Digital Media Art Key Laboratory of Sichuan ProvinceSichuan Conservatory of MusicChengduChina Department of Computer Science Rensselaer Polytechnic InstituteNew YorkNew YorkUSA

An excellent cardinality estimation can make the query optimiser produce a good execution *** there are some studies on cardinality estimation,the prediction results of existing cardinality estimators are inaccurate and the query efficiency cannot be guaranteed as *** particular,they are difficult to accurately obtain the complex relationships between multiple tables in complex database *** dealing with complex queries,the existing cardinality estimators cannot achieve good *** this study,a novel cardinality estimator is *** uses the core techniques with the BiLSTM network structure and adds the attention ***,the columns involved in the query statements in the training set are sampled and compressed into ***,the Word2vec model is used to embed the word vectors about the query ***,the BiLSTM network and attention mechanism are employed to deal with word *** proposed model takes into consideration not only the correlation between tables but also the processing of complex *** experiments and the evaluation of BiLSTM-Attention Cardinality Estimator(BACE)on the IMDB datasets are *** 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.

关键词： attention BiLSTM cardinality estimation complex database systems query optimiser Word2vec

Key techniques for predicting the uncertain trajectories of moving objects with dynamic environment awareness

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Journal of Modern Transportation 2011年第3期19卷 199-206页

作者： shaojie qiao Xian WANG Lu＇an TANG Liangxu LIU Xun GONG School of Information Science and Technology Southwest Jiaotong UniversityChengdu 610031China Department of Computer Science University of Illinois at Urbana-ChampaignUrbana 61801USA School of Electronics and Information Engineering Ningbo University of TechnologyNingbo 315016China

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 *** to accurately predict the uncertain mobility of objects becomes an important and challenging *** 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 *** 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 *** 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 *** conducted on synthetic trajectory data verify the effectiveness of the improved algorithm,which also guarantees the time performance as well.

关键词： trajectory prediction moving objects databases dynamic environmental factors continuous time Bayesian networks

谐振式硅微结构压力传感器非线性振动特性研究

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仪器仪表学报 2006年第12期27卷 1670-1673页

作者：樊尚春乔少杰张轩北京航空航天大学仪器科学与光电工程学院北京100083

本文研究了谐振式硅微结构压力传感器在单频激励和双频激励情况下的非线性振动特性。利用多尺度法研究运动方程中三次非线性项对传感器频率特性的影响规律,提出了改善谐振式硅微结构传感器特性的方法以及在实现闭环自激系统时应采取的... 详细信息

本文研究了谐振式硅微结构压力传感器在单频激励和双频激励情况下的非线性振动特性。利用多尺度法研究运动方程中三次非线性项对传感器频率特性的影响规律,提出了改善谐振式硅微结构传感器特性的方法以及在实现闭环自激系统时应采取的措施。

关键词：非线性振动多尺度法压力传感器硅微结构

Cooperation Oriented Computing:A Computing Model Based on Emergent Dynamics of Group Cooperation

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国际计算机前沿大会会议论文集 2015年第B12期 55-57页

作者： Jiaoling Zheng Hongpin Shu Yuanping Xu shaojie qiao Liyu Wen Department of Software Engineering Chengdu University of Information TechnologyNo.24Block 1Xuefu RoadChengdu 610225China

Traditional way of problem solving tries to deliver data to *** when the problem’s complexity exponentially increases as the data scale increases,to obtain the solution is *** cooperation computing model works in an inverse way by delivering program to *** first models each single data as individual and data unit as group of ***,different cooperation rules are designed for individuals to cooperate with each ***,the solution of the problem emerges through individuals’cooperation *** study applies group cooperation computing model to solve Hamilton Path problem which has NP-complete time *** results show that the cooperation model works much better than genetic *** 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 ***,the problem complexity may be exponent.

关键词： Group cooperation Cooperation rules Social computing Hamilton path NP-hard

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融合机器学习的移动数据挖掘技术导读

无线电通信技术 2023年第4期49卷 604-605页

作者：乔少杰成都信息工程大学

“十四五”时期,我国由工业经济迈向数字经济,数据上升为新的生产要素,是国家基础性战略资源。如何精确地挖掘移动数据中潜在价值对推动数据产业快速发展至关重要。机器学习是人工智能的核心,涉及统计学、系统辨识、逼近理论、神经网络... 详细信息

“十四五”时期,我国由工业经济迈向数字经济,数据上升为新的生产要素,是国家基础性战略资源。如何精确地挖掘移动数据中潜在价值对推动数据产业快速发展至关重要。机器学习是人工智能的核心,涉及统计学、系统辨识、逼近理论、神经网络、优化理论、计算机科学、脑科学等诸多领域,机器学习技术能够帮助各个行业更好地从其主要应用场景所获取的海量数据中“挖掘”关键信息,实现图像分类、实体识别、轨迹预测、风险预测、目标检测、交通检测等重要功能。融合机器学习的移动数据挖掘的研究已成为学术界和工业界的研究热点,亟需探索机器学习与移动数据挖掘的新理论与新技术,以推动相关产业落地应用。

关键词：机器学习计算机科学实体识别图像分类人工智能神经网络风险预测系统辨识

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基于中性突变的朴素基因表达式编程

计算机研究与发展 2010年第2期47卷 292-299页

作者：朱明放唐常杰代术成陈瑜乔少杰向勇江苏技术师范学院计算机工程学院江苏常州213001 四川大学计算机学院成都610065 西南交通大学信息科学与技术学院成都610031 成都电子机械高等专科学校计算机工程系成都610031

分子进化中性学说认为生物的进化主要是由中性突变决定的.基因表达式编程(GEP)是一种将基因型和表现型分离的新的进化模型,其突出表现在基因组存在不被表达的中性区.基于朴素基因表达式编程(NGEP)模型研究了NGEP中性区在进化中的作用.... 详细信息

分子进化中性学说认为生物的进化主要是由中性突变决定的.基因表达式编程(GEP)是一种将基因型和表现型分离的新的进化模型,其突出表现在基因组存在不被表达的中性区.基于朴素基因表达式编程(NGEP)模型研究了NGEP中性区在进化中的作用.主要工作包括:1)进一步完善了基于完全树编码方案的NGEP模型的概念;2)分析了传统GEP和NGEP的基因中性区域特点,指出NGEP存在更自由灵活的中性区域;3)通过控制基因长度和基因数量,调控中性区的大小和数量,研究了NGEP和传统GEP的中性区域在进化中的特殊作用,验证了NGEP的有效性;4)实验表明,在存在相同适度的中性区域条件下,NGEP比传统GEP进化更有效,且NGEP的成功率随中性区域的增加不会发生剧烈变化.

关键词：中性遗传中性区域基因表达式编程朴素基因表达式编程进化计算

面向车联网的自适应危险驾驶行为分析与预测框架

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无线电工程 2023年第6期53卷 1311-1320页

作者：黄江涛王鑫乔少杰南宁师范大学计算机与信息工程学院广西南宁530001 成都信息工程大学软件工程学院四川成都610225

危险驾驶行为分析与预测是智能交通领域中的研究热点,但现有的驾驶行为分析模型要素单一、环境适应性不足,不能客观评估危险驾驶风险程度。为了解决上述问题,提出一种面向车联网(Internet of Vehicles,IoV)的自适应危险驾驶行为分析与... 详细信息

危险驾驶行为分析与预测是智能交通领域中的研究热点,但现有的驾驶行为分析模型要素单一、环境适应性不足,不能客观评估危险驾驶风险程度。为了解决上述问题,提出一种面向车联网(Internet of Vehicles,IoV)的自适应危险驾驶行为分析与预测框架。对驾驶行为数据进行深度分析,总结危险驾驶的影响因素;提出一种新型基于模糊逻辑的危险驾驶风险评估算法,从宏观角度评估驾驶员当前危险驾驶的风险等级;提出一种基于DB-LSTM(Driving Behavior based Long-Short Term Memory)的危险驾驶风险预测算法,用于预测驾驶员下一阶段的危险驾驶程度;在DDD17真实IoV数据集上进行大量对比试验。实验结果表明,提出模型的性能优于其他主流方法,具有良好的准确性和可用性。

关键词：车联网危险驾驶行为大数据分析模糊逻辑长短时记忆

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新型融合注意力机制的遮挡面部表情识别框架

重庆理工大学学报（自然科学） 2023年第9期37卷 217-226页

作者：张本文高瑞玮乔少杰四川民族学院理工学院四川康定626001 成都信息工程大学软件工程学院成都610225

现有基于深度学习的面部表情识别模型不能有效地应对面部遮挡部分的干扰,无法准确捕捉面部未遮挡部分的特征,会导致识别准确率降低。为此,提出一种新型融合注意力机制的遮挡面部表情识别框架FER-AM(facial expression recognition frame... 详细信息

现有基于深度学习的面部表情识别模型不能有效地应对面部遮挡部分的干扰,无法准确捕捉面部未遮挡部分的特征,会导致识别准确率降低。为此,提出一种新型融合注意力机制的遮挡面部表情识别框架FER-AM(facial expression recognition framework based on attention mechanism),应用局部特征网络提取面部表情的局部关键特征,设计全局特征网络学习整个面部表情中的互补信息,采用注意力机制处理面部遮挡部分如眼镜、口罩和围巾等。在RAF-DB、AffectNet、CK+(Cohn Kanade)及FED-RO数据集进行大量实验,结果表明:FER-AM的7种表情分类性能均优于基于深度学习的代表性人脸面部表情识别模型,识别准确率达到88.1%。

关键词：遮挡面部表情识别特征提取特征分类深度学习注意力机制