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Xue LI,Pengjing LI,Dong WANG,Yuqiu WANG
《环境科学与工程前沿(英文)》 2014年 第8卷 第6期 页码 895-904 doi: 10.1007/s11783-014-0736-z
关键词: Xin'anjiang River multivariable statistical analysis temporal variation spatial variation water quality
Ali Reza GHANIZADEH, Morteza RAHROVAN
《结构与土木工程前沿(英文)》 2019年 第13卷 第4期 页码 787-799 doi: 10.1007/s11709-019-0516-8
关键词: full-depth reclamation soil-reclaimed asphalt pavement blend Portland cement unconfined compressive strength multivariate adaptive regression spline
三峡库区香溪河流域多变量生态水文风险的不确定性分析 Article
Yurui Fan,Guohe Huang,Yin Zhang,Yongping Li
《工程(英文)》 2018年 第4卷 第5期 页码 617-626 doi: 10.1016/j.eng.2018.06.006
本研究基于copula函数开发了一种多变量生态水文风险评估框架,用于分析三峡库区香溪河流域极端生态水文事件的发生频率。通过马尔可夫链蒙特卡罗(MCMC)方法量化边缘分布及copula函数中参数的不确定性,并基于后验概率揭示联合重现期的内在不确定性,同时可进一步得到双变量及多变量风险的概率特征。研究结果显示所得概率模型的预测区间可很好地匹配观测值,尤其对洪水持续时间而言。同时,“AND”联合重现期的不确定性随着单个洪水变量重现期的增加而增加。此外,低设计流量及高服务年限可能导致高洪水风险且伴随大量不确定性。
Hua Tao, Pinjing He, Yi Zhang, Wenjie Sun
《环境科学与工程前沿(英文)》 2017年 第11卷 第6期 doi: 10.1007/s11783-017-0945-3
关键词: Municipal solid waste Incineration Circulating fluidized bed Load change Multivariate outlier detection
Image-based fall detection and classification of a user with a walking support system
Sajjad TAGHVAEI, Kazuhiro KOSUGE
《机械工程前沿(英文)》 2018年 第13卷 第3期 页码 427-441 doi: 10.1007/s11465-017-0465-7
The classification of visual human action is important in the development of systems that interact with humans. This study investigates an image-based classification of the human state while using a walking support system to improve the safety and dependability of these systems. We categorize the possible human behavior while utilizing a walker robot into eight states (i.e., sitting, standing, walking, and five falling types), and propose two different methods, namely, normal distribution and hidden Markov models (HMMs), to detect and recognize these states. The visual feature for the state classification is the centroid position of the upper body, which is extracted from the user’s depth images. The first method shows that the centroid position follows a normal distribution while walking, which can be adopted to detect any non-walking state. The second method implements HMMs to detect and recognize these states. We then measure and compare the performance of both methods. The classification results are employed to control the motion of a passive-type walker (called “RT Walker”) by activating its brakes in non-walking states. Thus, the system can be used for sit/stand support and fall prevention. The experiments are performed with four subjects, including an experienced physiotherapist. Results show that the algorithm can be adapted to the new user’s motion pattern within 40 s, with a fall detection rate of 96.25% and state classification rate of 81.0%. The proposed method can be implemented to other abnormality detection/classification applications that employ depth image-sensing devices.
关键词: fall detection walking support hidden Markov model multivariate analysis
Spatio-temporal variations of water quality in Yuqiao Reservoir Basin, North China
Yuan XU,Ruqin XIE,Yuqiu WANG,Jian SHA
《环境科学与工程前沿(英文)》 2015年 第9卷 第4期 页码 649-664 doi: 10.1007/s11783-014-0702-9
关键词: Fuzzy comprehensive assessment multivariate statistical analysis water quality
Field investigation of intelligent compaction for hot mix asphalt resurfacing
Wei HU,Xiang SHU,Baoshan HUANG,Mark WOODS
《结构与土木工程前沿(英文)》 2017年 第11卷 第1期 页码 47-55 doi: 10.1007/s11709-016-0362-x
Intelligent compaction (IC) is a relatively new technology for asphalt paving industry. The present study evaluated the effectiveness and potential issues of the IC technology for flexible pavement resurfacing construction using two field projects. In the first project, a geostatistical semivariogram model was established and the parameters derived from it were compared with univariate statistical parameters for the Compaction Meter Value (CMV) data. Further analyses illustrated the effect of temperature on the CMV value and compaction uniformity. In the second project, a multivariate analysis was performed between in situ tests and IC data. The possibility of combining various IC data to predict the asphalt layer density and improve the current quality control and assurance system was discussed.
关键词: intelligent compaction compaction meter value (CMV) semivariogram multivariate analysis
陆化普,柏卓彤,吴洲豪,傅志寰
《中国工程科学》 2022年 第24卷 第6期 页码 146-153 doi: 10.15302/J-SSCAE-2022.06.013
超大特大城市中心城区高强度连片开发、人口密度大、城市功能集中,是我国城市问题表现最为突出的区域范围;着眼集中于中心城区的大城市病破解问题,开展超大特大城市中心城区的合理规模分析论证具有迫切性。本文提出了通勤出行时间是超大特大城市中心城区合理规模的核心控制因素这一基本判断;采用大数据分析及聚类分析方法,结合城市多类土地利用的兴趣点数据、街道行政边界的地理信息系统数据,识别了我国10 个超大特大城市的现状中心城区范围;基于网络地图路径规划、手机信令数据校核,分析评价了现状交通效率;以量化分析为基础,获得了特大城市中心城区合理规模的论证结果。研究表明,当前一些超大特大城市的中心城区范围不能满足以人为本的幸福通勤出行需求;结合未来交通运输领域技术发展、治理水平提高等因素,13~15 km当量半径是超大特大城市中心城区合理规模范围的上限。
一种直观的一般秩相关系数 Research Articles
Divya PANDOVE, Shivani GOEL, Rinkle RANI
《信息与电子工程前沿(英文)》 2018年 第19卷 第6期 页码 699-711 doi: 10.1631/FITEE.1601549
扩大多元回归方法在跨组学研究中的范围 Article
Xiaoxi Hu, Yue Ma, Yakun Xu, Peiyao Zhao, Jun Wang
《工程(英文)》 2021年 第7卷 第12期 页码 1725-1731 doi: 10.1016/j.eng.2020.05.028
近年来科技的进步和发展使得高维数据急剧增加,研究人员对合适且有效的多元回归方法的需求也随之增长。许多传统的多元分析方法如主成分分析等已广泛应用于投资分析、图像识别和群体遗传结构分析等研究领域。然而,这些常见的方法存在其局限性,即忽略了响应之间的相关性和变量选择效率低的问题。因此,本文引入了降秩回归方法及其扩展形式——稀疏降秩回归和行稀疏的子空间辅助回归,这些方法有望满足上述需求,从而提高回归模型的可解释性。我们通过开展仿真研究来评估它们的效果,并将它们与其他几种变量选择方法进行比较。对于不同的应用场景,我们也提供了基于预测能力和变量选择精度的选择建议。最后,为了证明这些方法在微生物组研究领域的实用价值,我们将所选择的方法应用于实际种群水平的微生物组数据,结果验证了我们方法的有效性。该方法的扩展形式为未来的组学研究特别是多元回归研究提供了有价值的指导,并为微生物组学及其相关研究领域的新发现奠定了基础。
《能源前沿(英文)》 2023年 第17卷 第4期 页码 527-544 doi: 10.1007/s11708-023-0880-x
关键词: fault detection unary classification self-supervised representation learning multivariate nonlinear time series
基于回归预测集成学习的交互式图像分割 Article
Jin ZHANG, Zhao-hui TANG, Wei-hua GUI, Qing CHEN, Jin-ping LIU
《信息与电子工程前沿(英文)》 2017年 第18卷 第7期 页码 1002-1020 doi: 10.1631/FITEE.1601401
Decomposition analysis applied to energy and emissions: A literature review
《工程管理前沿(英文)》 页码 625-639 doi: 10.1007/s42524-023-0270-4
关键词: index decomposition analysis structural decomposition analysis production decomposition analysis energy CO2 emissions
B. VIDHYA,K. N. SRINIVAS
《能源前沿(英文)》 2016年 第10卷 第4期 页码 424-440 doi: 10.1007/s11708-016-0423-9
关键词: flux reversal generator air velocity computation fluid dynamics thermal analysis vibration analysis finite element analysis
标题 作者 时间 类型 操作
Assessment of temporal and spatial variations in water quality using multivariate statistical methods
Xue LI,Pengjing LI,Dong WANG,Yuqiu WANG
期刊论文
Modeling of unconfined compressive strength of soil-RAP blend stabilized with Portland cement using multivariate
Ali Reza GHANIZADEH, Morteza RAHROVAN
期刊论文
Performance evaluation of circulating fluidized bed incineration of municipal solid waste by multivariate
Hua Tao, Pinjing He, Yi Zhang, Wenjie Sun
期刊论文
Image-based fall detection and classification of a user with a walking support system
Sajjad TAGHVAEI, Kazuhiro KOSUGE
期刊论文
Spatio-temporal variations of water quality in Yuqiao Reservoir Basin, North China
Yuan XU,Ruqin XIE,Yuqiu WANG,Jian SHA
期刊论文
Field investigation of intelligent compaction for hot mix asphalt resurfacing
Wei HU,Xiang SHU,Baoshan HUANG,Mark WOODS
期刊论文
Unknown fault detection for EGT multi-temperature signals based on self-supervised feature learning and unary classification
期刊论文