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Variation characteristics of atmospheric methane and carbon dioxide in summertime at a coastal site in the South China Sea

《环境科学与工程前沿（英文）》 2022年第16卷第11期 doi: 10.1007/s11783-022-1574-z

摘要：

● Diurnal patterns of CH₄ and CO₂ are clearly extracted using EEMD.

关键词： Methane Carbon dioxide Diurnal pattern Ensemble empirical mode decomposition South China Sea Sea breeze

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Relative vibration identification of cutter and workpiece based on improved bidimensional empirical modedecomposition

Jiasheng LI, Xingzhan LI, Wei WEI, Pinkuan LIU

《机械工程前沿（英文）》 2020年第15卷第2期页码 227-239 doi: 10.1007/s11465-020-0587-1

摘要： In the process of cutting, the relative vibration between the cutter and the workpiece has an important effect on the surface topography. In this study, the bidimensional empirical mode decomposition (BEMD) method is used to identify such effect. According to Riesz transform theory, a type of isotropic monogenic signal is proposed. The boundary data is extended on the basis of a similarity principle that deals with serious boundary effect problem. The decomposition examples show that the improved BEMD can effectively solve the problem of boundary effect and decompose the original machined surface topography at multiple scales. The characteristic surface topography representing the relative vibration between the cutter and the workpiece through feature identification is selected. In addition, the spatial spectrum analysis of the extracted profile is carried out. The decimal part of the frequency ratio that has an important effect on the shape of the contour can be accurately identified through contour extraction and spatial spectrum analysis. The decomposition results of simulation and experimental surface morphology demonstrate the validity of the improved BEMD algorithm in realizing the relative vibration identification between the cutter and the workpiece.

关键词： bidimensional empirical mode decomposition spatial spectrum analysis boundary effect vibration identification surface topography

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基于Spark面向分布式EEMDN-SABiGRU模型的乘客热点预测

夏大文,耿建,黄瑞曦,申冰琪,胡杨,李艳涛,李华青

《信息与电子工程前沿（英文）》 2023年第24卷第9期页码 1316-1331 doi: 10.1631/FITEE.2200621

摘要：针对出租车与乘客之间的供需不平衡问题，本文提出一种基于Spark的分布式归一化集合经验模态分解和面向空间注意力机制的双向门控循环单元（EEMDN-SABiGRU）模型，实现乘客热点的精准预测，旨在于降低盲目巡航开支、提高载客效率和实现收益最大化。首先，提出一种归一化的集合经验模态分解方法（EEMDN），处理网格中乘客热点数据，解决非平稳序列问题和数值差异过大造成的预测精度下降问题，避免EMD本征模态函数（IMF）存在的模态混叠现象。其次，构建一种基于乘客上下车热点的权重和乘客的空间规律性的空间注意力机制，捕捉每个网格中的乘客热点特征。再次，融合一种双向门控循环单元（GRU）算法，解决GRU仅能获取前向信息而忽略后向信息问题，提高特征提取的准确性。最后，在Spark并行计算框架下，采用真实的出租车GPS轨迹数据，基于EEMDN-SABiGRU模型实现了乘客热点的准确预测。实验结果表明，在00网格4个数据集上，与LSTM、EMDL-STM、EEMD-LSTM、GRU、EMD-GRU、EEMD-GRU、EMDN-GRU、CNN和BP相比，EEMDN-SABiGRU的平均绝对百分比误差、平均绝对误差、均方根误差和最大误差值分别降低了43.18%、44.91%、55.04%和39.33%。

关键词：乘客热点预测集合经验模态分解（EEMD）空间注意力机制双向门控循环单元（BiGRU） GPS轨迹 Spark

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一种基于多因素分析和多模型集成的海洋溶解氧浓度时间序列预测混合神经网络模型 Article

刘辉, 杨睿, 段铸, 吴海平

《工程（英文）》 2021年第7卷第12期页码 1751-1765 doi: 10.1016/j.eng.2020.10.023

摘要：

溶解氧是水产养殖的重要指标，准确预测溶解氧浓度可有效提高水产品质量。本文提出了一种新的溶解氧混合预测模型，该模型包括多因素分析、自适应分解和优化集成三个阶段。首先，考虑到影响溶解氧浓度的因素复杂繁多，采用灰色关联度法筛选出与溶解氧关系最密切的环境因素，多因素的考虑使得模型融合更加有效。其次，运用经验小波变换方法自适应地将溶解氧、水温、盐度和氧饱和度等序列分解为子序列。然后，利用5个基准模型对经验小波变换分解出的子序列进行预测，这五个子预测模型的集成权重通过粒子群优化和引力搜索算法计算得出。最后，通过加权分配得到溶解氧多因素集成模型。来自太平洋岛屿海洋观测系统希洛WQB04站收集的时间序列数据验证了该模型的性能。实验的评价指标包括Nash-Sutcliffe效率系数、Kling-Gupta效率系数、平均绝对百分比误差、误差标准差和决定系数。实例分析表明：①所提出的模型能够获得优异的溶解氧预测结果；②该模型优于文中其他对比模型；③预测模型可用于分析溶解氧变化趋势，便于管理者能够做出更好的决策。

关键词：溶解氧浓度预测时间序列多步预测多因素分析经验小波变化分解多模型优化集成

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Variational mode decomposition based modal parameter identification in civil engineering

Mingjie ZHANG, Fuyou XU

《结构与土木工程前沿（英文）》 2019年第13卷第5期页码 1082-1094 doi: 10.1007/s11709-019-0537-3

摘要： An out-put only modal parameter identification method based on variational mode decomposition (VMD) is developed for civil structure identifications. The recently developed VMD technique is utilized to decompose the free decay response (FDR) of a structure into to modal responses. A novel procedure is developed to calculate the instantaneous modal frequencies and instantaneous modal damping ratios. The proposed identification method can straightforwardly extract the mode shape vectors using the modal responses extracted from the FDRs at all available sensors on the structure. A series of numerical and experimental case studies are conducted to demonstrate the efficiency and highlight the superiority of the proposed method in modal parameter identification using both free vibration and ambient vibration data. The results of the present method are compared with those of the empirical mode decomposition-based method, and the superiorities of the present method are verified. The proposed method is proved to be efficient and accurate in modal parameter identification for both linear and nonlinear civil structures, including structures with closely spaced modes, sudden modal parameter variation, and amplitude-dependent modal parameters, etc.

关键词： modal parameter identification variational mode decomposition civil structure nonlinear system closely spaced modes

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基于经验模式分解的旋转机械振动信号降噪处理

杨建文,贾民平,许飞云,胡建中

《中国工程科学》 2005年第7卷第8期页码 66-69

摘要：

分析了经验模式分解的滤波性能；针对旋转机械振动信号信噪比低及非平稳特性，应用经验模式分解对振动信号进行降噪处理，突出了有用振动信号，为旋转机械在线监测和故障诊断提供了有效的依据；仿真实验及真实数据分析表明，经验模式分解在振动信号降噪处理中是有效的，为振动信号分析提供了新的方法。

关键词：故障诊断经验模式分解旋转机械滤波

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Robust ensemble of metamodels based on the hybrid error measure

《机械工程前沿（英文）》 2021年第16卷第3期页码 623-634 doi: 10.1007/s11465-021-0641-7

摘要： Metamodels have been widely used as an alternative for expensive physical experiments or complex, time-consuming computational simulations to provide a fast but accurate analysis. However, challenge remains in the prior determination of the most suitable metamodel for a particular case because of the lack of information about the actual behavior of a system. In addition, existing studies on metamodels have largely restricted on solving deterministic problems (e.g., data from finite element models), whereas some real-life engineering problems (e.g., data from physical experiment) are stochastic problems with noisy data. In this work, a robust ensemble of metamodels (EMs) is proposed by combining three regression stand-alone metamodels in a weighted sum form. The weight factor is adaptively determined according to the hybrid error metric, which combines global and local error measures to improve the accuracy of the EMs. Furthermore, three typical individual metamodels that can filter noise are selected to construct the EMs to extend their application in practical engineering problems. Three well-known benchmark problems with different levels of noise and three engineering problems are used to verify the effectiveness of the proposed EMs. Results show that the proposed EMs have higher accuracy and robustness than the individual metamodels and other typical EMs in major cases.

关键词： metamodel ensemble of metamodels hybrid error measure stochastic problem

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Trend detection and stochastic simulation prediction of streamflow at Yingluoxia hydrological station, Heihe River Basin, China

Chenglong ZHANG,Mo LI,Ping GUO

《农业科学与工程前沿（英文）》 2017年第4卷第1期页码 81-96 doi: 10.15302/J-FASE-2016112

摘要： Investigating long-term variation and prediction of streamflow are critical to regional water resource management and planning. Under the continuous influence of climate change and human activity, the trends of hydrologic time series are nonstationary, and consequently the established methods for hydrological frequency analysis are no longer applicable. Five methods, including the linear regression, nonlinear regression, change point analysis, wavelet analysis and Hilbert-Huang transformation, were first selected to detect and identify the deterministic and stochastic components of streamflow. The results indicated there was a significant long-term increasing trend. To test the applicability of these five methods, a comprehensive weighted index was then used to assess their performance. This index showed that the linear regression was the best method. Secondly, using the normality test for stochastic components separated by the linear regression method, a normal distribution requirement was satisfied. Next, the Monte Carlo stochastic simulation technique was used to simulate these stochastic components with normal distribution, and thus a new ensemble hydrological time series was obtained by combining the corresponding deterministic components. Finally, according to these outcomes, the streamflow at different frequencies in 2020 was predicted.

关键词： Monte Carlo nonstationary trend detection streamflow prediction decomposition and ensemble Yingluoxia

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Processing parameter optimization of fiber laser beam welding using an ensemble of metamodels and MOABC

《机械工程前沿（英文）》 2022年第17卷第4期 doi: 10.1007/s11465-022-0703-5

摘要： In fiber laser beam welding (LBW), the selection of optimal processing parameters is challenging and plays a key role in improving the bead geometry and welding quality. This study proposes a multi-objective optimization framework by combining an ensemble of metamodels (EMs) with the multi-objective artificial bee colony algorithm (MOABC) to identify the optimal welding parameters. An inverse proportional weighting method that considers the leave-one-out prediction error is presented to construct EM, which incorporates the competitive strengths of three metamodels. EM constructs the correlation between processing parameters (laser power, welding speed, and distance defocus) and bead geometries (bead width, depth of penetration, neck width, and neck depth) with average errors of 10.95%, 7.04%, 7.63%, and 8.62%, respectively. On the basis of EM, MOABC is employed to approximate the Pareto front, and verification experiments show that the relative errors are less than 14.67%. Furthermore, the main effect and the interaction effect of processing parameters on bead geometries are studied. Results demonstrate that the proposed EM-MOABC is effective in guiding actual fiber LBW applications.

关键词： laser beam welding parameter optimization metamodel multi-objective

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A novel hybrid model for water quality prediction based on VMD and IGOA optimized for LSTM

《环境科学与工程前沿（英文）》 2023年第17卷第7期 doi: 10.1007/s11783-023-1688-y

摘要：

● A novel VMD-IGOA-LSTM model has proposed for the prediction of water quality.

关键词： Water quality prediction Grasshopper optimization algorithm Variational mode decomposition Long short-term memory neural network

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Prediction of the theoretical and semi-empirical model of ambient temperature

Foued CHABANE,Noureddine MOUMMI,Abdelhafid BRIMA,Abdelhafid MOUMMI

《能源前沿（英文）》 2016年第10卷第3期页码 268-276 doi: 10.1007/s11708-016-0413-y

摘要： It is well known that the ambient temperature is a sensitive parameter which has a great effect on biology, technology, geology and even on human behavior. A prediction is a statement about an uncertain event. It is often, but not always, based upon experience or knowledge. Although guaranteed accurate information about the future is in many cases impossible, prediction can be useful to assist in making plans about possible developments. As a result, temperature profiles can be developed which accurately represent the expected ambient temperature exposure that this environment experiences during measurement. The ambient temperature over time is modeled based on the previous and data and using a Lagrange interpolation. To observe the comprehensive variation of ambient temperature the profile must be determined numerically. The model proposed in this paper can provide an acceptable way to measure the change in ambient temperature.

关键词： ambient temperature environment correlation theoretical model semi-empirical

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Detection of schedule delay risk of empirical construction projects

Tsegay GEBREHIWET, Hanbin LUO

《工程管理前沿（英文）》 2018年第5卷第2期页码 251-267 doi: 10.15302/J-FEM-2018086

摘要： In Ethiopian construction projects, schedule delay risk is a predominant issue because it is not properly addressed. Although several studies have been focused on the various effects of risk in construction projects, limited efforts have been made to investigate the typical and the overall schedule delay risk. In this study, our aim is to detect the typical and overall schedule delay risk throughout the construction project lifecycle, which consists of the pre-construction, construction, and post-construction stages, and compare the stages with each other. Common criteria, sub-criteria, and attributes were developed for all alternatives for the purpose of making a risk decision. The methodology that was followed integrated the multiple-criteria decision-making (MCDM) model of fuzzy analytic hierarchy process comprehensive evaluation (FAHPCE) and the relative important index (RII). Data were collected from 77 participants, who were selected through purposive sampling from different contracting organizations in Ethiopian construction projects by means of questionnaires that were distributed to experienced experts. The findings showed that there is a typical delay risk either in the type or in the level of the different construction activities. Consequently, the most influenced alternative is the construction stage because of the high-risk responsibility, resource, and contract condition related criteria. The post-construction stage was the second most influenced stage because of the high-risk responsibility-related criteria. The pre-constructed stage was the least influenced stage that consist high-risk criteria of responsibility, resource, and contract condition related. These differences provided noteworthy information about risk mitigation in construction projects by identifying the exact risk level on specific activity to make appropriate decision.

关键词： fuzzy analytic hierarchy process comprehensive evaluation construction project detection of delay risk relative important index

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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

摘要： Decomposition analysis has been widely used to assess the determinants of energy and CO₂ emissions in academic research and policy studies. Both the methodology and application of decomposition analysis have been largely improved in the past decades. After more than 50 years’ developments, decomposition studies have become increasingly sophisticated and diversified, and tend to converge internally and integrate with other analytical approaches externally. A good understanding of the literature and state of the art is critical to identify knowledge gaps and formulate future research agenda. To this end, this study presents a literature survey for decomposition analysis applied to energy and emission issues, with a focus on the period of 2016–2021. A review for three individual decomposition techniques is first conducted, followed by a synthesis of emerging trends and features for the decomposition analysis literature as a whole. The findings are expected to direct future research in decomposition analysis.

关键词： index decomposition analysis structural decomposition analysis production decomposition analysis energy CO₂ emissions

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Optimization design of anti-seismic engineering measures for intake tower based on non-dominated sorting genetic algorithm-II

《结构与土木工程前沿（英文）》页码 1428-1441 doi: 10.1007/s11709-023-0998-2

摘要： High-rise intake towers in high-intensity seismic areas are prone to structural safety problems under vibration. Therefore, effective and low-cost anti-seismic engineering measures must be designed for protection. An intake tower in northwest China was considered the research object, and its natural vibration characteristics and dynamic response were first analyzed using the mode decomposition response spectrum method based on a three-dimensional finite element model. The non-dominated sorting genetic algorithm-II (NSGA-II) was adopted to optimize the anti-seismic scheme combination by comprehensively considering the dynamic tower response and variable project cost. Finally, the rationality of the original intake tower antiseismic design scheme was evaluated according to the obtained optimal solution set, and recommendations for improvement were proposed. The method adopted in this study may provide significant references for designing anti-seismic measures for high-rise structures such as intake towers located in high-intensity earthquake areas.

关键词： intake tower NSGA-II mode decomposition response spectrum method anti-seismic engineering measures optimization design variable project cost

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Efficient Identification of water conveyance tunnels siltation based on ensemble deep learning

Xinbin WU; Junjie LI; Linlin WANG

《结构与土木工程前沿（英文）》 2022年第16卷第5期页码 564-575 doi: 10.1007/s11709-022-0829-x

摘要： The inspection of water conveyance tunnels plays an important role in water diversion projects. Siltation is an essential factor threatening the safety of water conveyance tunnels. Accurate and efficient identification of such siltation can reduce risks and enhance safety and reliability of these projects. The remotely operated vehicle (ROV) can detect such siltation. However, it needs to improve its intelligent recognition of image data it obtains. This paper introduces the idea of ensemble deep learning. Based on the VGG16 network, a compact convolutional neural network (CNN) is designed as a primary learner, called Silt-net, which is used to identify the siltation images. At the same time, the fully-connected network is applied as the meta-learner, and stacking ensemble learning is combined with the outputs of the primary classifiers to obtain satisfactory classification results. Finally, several evaluation metrics are used to measure the performance of the proposed method. The experimental results on the siltation dataset show that the classification accuracy of the proposed method reaches 97.2%, which is far better than the accuracy of other classifiers. Furthermore, the proposed method can weigh the accuracy and model complexity on a platform with limited computing resources.

关键词： water conveyance tunnels siltation images remotely operated vehicles deep learning ensemble learning computer vision