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Heterogeneous information phase space reconstruction and stability prediction of filling body–surrounding rock combination

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International Journal of Minerals,Metallurgy and Materials 2024年第7期31卷 1500-1511页

作者： Dapeng Chen Shenghua Yin Weiguo Long Rongfu yan Yufei Zhang Zepeng yan leiming Wang Wei Chen School of Civil and Resources Engineering University of Science and Technology of BeijingBeijing 100083China Production Technology Department Longshou MineJinchuan Group Co.Ltd.Jinchang 737100China School of Civil Engineering and Architecture East China Jiaotong UniversityNanchang 330013China

Traditional research believes that the filling body can effectively control stress concentration while ignoring the problems of unknown stability and the complex and changeable stress distribution of the filling body–surrounding rock combination under high-stress *** monitoring data processing methods cannot fully consider the complexity of monitoring objects,the diversity of monitoring methods,and the dynamics of monitoring *** solve this problem,this paper proposes a phase space reconstruction and stability prediction method to process heterogeneous information of backfill–surrounding rock *** three-dimensional monitoring system of a large-area filling body–surrounding rock combination in Longshou Mine was constructed by using drilling stress,multipoint displacement meter,and *** information,such as the stress and displacement of the filling body–surrounding rock combination,was continuously *** with the average mutual information method and the false nearest neighbor point method,the phase space of the heterogeneous information of the filling body–surrounding rock combination was then *** this paper,the distance between the phase point and its nearest point was used as the index evaluation distance to evaluate the stability of the filling body–surrounding rock *** evaluated distances(ED)revealed a high sensitivity to the stability of the filling body–surrounding rock *** new method was then applied to calculate the time series of historically ED for 12 measuring points located at Longshou *** moments of mutation in these time series were at least 3 months ahead of the roadway return *** the ED prediction experiments,the autoregressive integrated moving average model showed a higher prediction accuracy than the deep learning models(long short-term memory and Transformer).Furthermore,the root-mean-square error distribution of the prediction results peaked at 0

关键词： deep mining filling body–surrounding rock combination phase space reconstruction multiple time series stability prediction

XGBoost Algorithm under Differential Privacy Protection

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Journal of Information Hiding and Privacy Protection 2021年第1期3卷 9-16页

作者： Yuanmin Shi Siran Yin Ze Chen leiming yan School of Computer&Software Nanjing University of Information Science&TechnologyNanjingChina Engineering Research Center of Digital Forensics Ministry of EducationNanjingChina

Privacy protection is a hot research topic in information security *** improved XGBoost algorithm is proposed to protect the privacy in classification *** combining with differential privacy protection,the XGBoost can improve the classification accuracy while protecting privacy *** using CART regression tree to build a single decision tree,noise is added according to Laplace *** with random forest algorithm,this algorithm can reduce computation cost and prevent overfitting to a certain *** experimental results show that the proposed algorithm is more effective than other traditional algorithms while protecting the privacy information in training data.

关键词： Differential privacy privacy protection XGBoost algorithm CART regression tree

Direct synthesis of hollow polyhedral ceria nano powders via a template-free mixed solvothermal route

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Journal of Rare Earths 2015年第8期33卷 892-897页

作者：刘俊亮颜雷鸣陈秀雷王绳芸张明田长安 School of Chemistry and Chemical Engineering Yangzhou University Key Laboratory of Environmental Materials and Engineering of Jiangsu Province Testing Center Yangzhou University Department of Chemistry and Materials Engineering Hefei University

Novel mono-dispersed hollow polyhedral ceria nano powders with the average particle size of 250 nm were directly synthesized via a simple template-free mixed solvothermal method by using water-ethanol as the solvent. The formation of such hollow structure with the regular polyhedral particle shape was based on a solvent-controlled Ostwald ripening coupled self-templating process. The mixed solvent promoted the formation of the regular solid particles at the beginning of solvothermal reaction and drove the Ostwald ripening as the reaction went on. Owing to the Ostwald ripening and self-assembly of nano crystallites, ceria nano particles converted into the hollow structures with regular polyhedral shape during the solvothermal process just by increasing solvothermal reaction time. The as-synthesized hollow ceria nano powders exhibited strong absorptions in the UV-vis spectrum and the evaluated energy band gaps increased according to the shape evolution and size decrease of the nano particles, which demonstrated obvious blue shift effects.

关键词： ceria hollow structures nano powders solvothermal reaction rare earths

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一种时序数据局部相关对象聚类算法

东南大学学报（自然科学版） 2007年第5期37卷 793-797页

作者：闫雷鸣孙志挥张柏礼东南大学计算机科学与工程学院南京210096

针对高维时序数据中局部相关模式的聚类问题,建立了一种基于相关子模式的spCluster模型,讨论了该模型与平均平方残值的关系.并以此模型为基础,提出了适用于时序数据的确定性双聚类算法sp-TSC,该算法首先利用spCluster模型将局部相关的... 详细信息

针对高维时序数据中局部相关模式的聚类问题,建立了一种基于相关子模式的spCluster模型,讨论了该模型与平均平方残值的关系.并以此模型为基础,提出了适用于时序数据的确定性双聚类算法sp-TSC,该算法首先利用spCluster模型将局部相关的数据对象符号化,然后将字符序列插入到泛化后缀树中,利用后缀树的性质避免了穷举局部相关子模式的各种组合,有效减小了搜索空间,从而可以在数据矩阵尺寸的线性时间内发现全部最大δ-spCluster.理论分析和实验表明,该算法是高效可行的.

关键词：双聚类时间序列后缀树局部相关

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基于句式元学习的Twitter分类

北京大学学报（自然科学版） 2019年第1期55卷 98-104页

作者：闫雷鸣严璐绮王超智贺嘉会吴宏煜南京信息工程大学计算机与软件学院江苏省网络监控工程中心南京210044

针对多类别的社交媒体短文本分类准确率较低问题,提出一种学习多种句式的元学习方法,用于改善Twitter文本分类性能。将Twitter文本聚类为多种句式,各句式结合原类标签,成为多样化的新类别,从而原分类问题转化为较多类别的few-shot学习问... 详细信息

针对多类别的社交媒体短文本分类准确率较低问题,提出一种学习多种句式的元学习方法,用于改善Twitter文本分类性能。将Twitter文本聚类为多种句式,各句式结合原类标签,成为多样化的新类别,从而原分类问题转化为较多类别的few-shot学习问题,并通过训练深层网络来学习句式原型编码。用多个三分类Twitter数据来检验所提Meta-CNN方法 ,结果显示,该方法的学习策略简单有效,即便在样本数量不多的情况下,与传统机器学习分类器和部分深度学习分类方法相比,Meta-CNN仍能获得较好的分类准确率和较高的F1值。

关键词：元学习少次学习情感分析卷积神经网络

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一种基于二次互信息的双聚类算法

计算机工程与应用 2006年第22期42卷 158-160页

作者：闫雷鸣孙志挥东南大学计算机科学与工程系南京210096

双聚类模型有助于聚类存在相关性的局部模式。论文提出了一种可识别多种相关模式的双聚类算法,以二次互信息作为相关性标准,并以Parzen窗口法有效估算高维变量之间的互信息;同时提出了最大相关维簇的概念。算法以多个最大相关维簇为种子... 详细信息

双聚类模型有助于聚类存在相关性的局部模式。论文提出了一种可识别多种相关模式的双聚类算法,以二次互信息作为相关性标准,并以Parzen窗口法有效估算高维变量之间的互信息;同时提出了最大相关维簇的概念。算法以多个最大相关维簇为种子,通过迭代细化聚类,可有效地发现高维数据环境内相关的长模式。真实基因表达数据的实验证明了算法的有效性。

关键词：双聚类二次互信息基因表达数据

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联合聚类非线性相关的时序基因表达数据

计算机研究与发展 2008年第11期45卷 1865-1873页

作者：闫雷鸣孙志挥吴英杰张柏礼东南大学计算机科学与工程学院南京210096

为聚类非线性相关的数据对象,引入广义信息论中二次互信息作为相似性度量,利用矩阵理论降低了二次互信息的计算量,并结合滑动窗口技术,建立了一种时序数据非线性相关模型.在此基础上提出了适用于时序基因表达数据的确定性联合聚类算法MI... 详细信息

为聚类非线性相关的数据对象,引入广义信息论中二次互信息作为相似性度量,利用矩阵理论降低了二次互信息的计算量,并结合滑动窗口技术,建立了一种时序数据非线性相关模型.在此基础上提出了适用于时序基因表达数据的确定性联合聚类算法MI-TSB.该算法将时序数据转化为抽象字符序列,然后插入到MI-泛化后缀树中,避免了穷举各种组合,从而快速索引全部聚类结果.实验结果显示MI-TSB算法具有良好的运行性能,成功聚类出非线性相关的对象;利用Gene Ontology对聚类结果进行基因注释,也验证了聚类结果的生物学意义.

关键词：二次互信息非线性相关联合聚类生物信息学基因表达数据

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影响滩涂淤泥早期固化强度的多因子正交分析

环境工程学报 2017年第8期11卷 4766-4774页

作者：严雷鸣祝建中朱晓强陈立程伦旭浅水湖泊综合治理与资源开发教育部重点实验室河海大学环境学院南京210098

选取南通某滩涂疏浚淤泥,实验研究初始含水率、含盐量、初始pH和有机质含量等4个关键物化因子对滩涂淤泥的水泥固化早期无侧限抗压强度(UCS)的影响,并对影响机理进行了分析。结果表明,淤泥初始含水率越高,固化土的UCS相应越低;Cl-和SO_4... 详细信息

选取南通某滩涂疏浚淤泥,实验研究初始含水率、含盐量、初始pH和有机质含量等4个关键物化因子对滩涂淤泥的水泥固化早期无侧限抗压强度(UCS)的影响,并对影响机理进行了分析。结果表明,淤泥初始含水率越高,固化土的UCS相应越低;Cl-和SO_4^(2-)含量对早期UCS的影响存在临界值,分别为13.55 g·kg^(-1)和8.71 g·kg^(-1),在对应临界值内,3d和7 d UCS均随着离子含量的增加而升高,具有早强效果,超过临界值后,UCS均随着离子含量的增加而降低;淤泥初始pH的升高有利于早期固化强度的增长;有机质含量对早期UCS的影响并不显著。五因素四水平正交实验分析表明,各因素对早期强度的影响大小为:初始含水率>Cl-含量>初始pH>SO_4^(2-)含量>有机质含量,初始含水率的影响最为显著。该研究结果对淤泥的进一步快速固化研究具有重要的意义。

关键词：含水率含盐量 pH 有机质早期抗压强度正交分析快速固化

T_GRASP: Optimization Algorithm of Ship Avoiding Typhoon Route

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Journal of Quantum Computing 2022年第2期4卷 85-95页

作者： Yingxian Huang Xueyan Ding yanan Zhang leiming yan Nanjing University of Information Science&Technology Nanjing210044China

AGRASP-based algorithm called T_GRASP for avoiding typhoon route optimization is suggested to increase the security and effectiveness of ship *** of the worst natural calamities that can disrupt a ship’s navigation and result in numerous safety mishaps is a ***,the captains manually review the collected weather data and steer clear of typhoons using their navigational *** distribution of heavy winds andwaves produced by the typhoon also changes dynamically as a result of the surrounding large-scale air pressure distribution,which significantly enhances the challenge of the captain’s preparation for avoiding typhoon *** is now necessary to find a solution to the challenge of designing a highsafety and effective ship navigation path to avoid *** T_GRASP algorithm is suggested to optimize the candidate set’s structure based on the GRASP algorithm’s *** algorithm can guarantee the safety of the ship to avoid typhoons and assure high route efficiency by using the lowest risk function,the shortest sailing time,and the least fuel consumption as the objective functions and the ship speed and highest safety as the model *** outcomes of the simulation demonstrate the superiority of the suggested T_GRASP algorithm over both the conventional A∗algorithm and the ant colony *** addition to addressing issues with the traditional A∗algorithm,like its wide search space and poor efficiency,the proposed algorithm also addresses issues with the ant colony algorithm,like its excessive iterations and sluggish convergence.

关键词： Ship voyage optimization weather routing avoiding typhoon A∗ grasp ant colony algorithm