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Long-term exposure to air pollution and cerebrovascular disease: findings from Beijing Health Management Cohort study

《环境科学与工程前沿（英文）》 2023年 第17卷 第7期 doi: 10.1007/s11783-023-1684-2

摘要：

● This study explored the long-term association by double robust additive models.

关键词： Air pollution     Cerebrovascular disease     Incidence     Long-term exposure     Doubly robust additive model    

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Robust control based on the Lyapunov theory of a grid-connected doubly fed induction generator

Ridha CHEIKH, Arezki MENACER, Said DRID

《能源前沿（英文）》 2013年 第7卷 第2期   页码 191-196 doi: 10.1007/s11708-013-0245-y

摘要： This paper discusses the robust control of a grid-connected doubly-fed induction generator (DFIG) controlled by vector control using a nonlinear feedback linearization strategy in order to ameliorate the performances of the control and to govern the developed stator active and reactive power in a linear and decoupled manner, in which an optimal operation of the DFIG in sub-synchronous operation is given, as well as the control stator power flow with the possibility of keeping stator power factor at a unity. The use of the state-all-flux induction machine model gives place to a simpler control model. So, to achieve this objective, the Lyapunov approach is used associated with a sliding mode control to guarantee the global asymptotical stability and the robustness of the parametric variations.

关键词： doubly fed induction generator (DFIG)     vector control     Lyapunov function     power factor unity     active power     reactive power    

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Robust direct power control based on the Lyapunov theory of a grid-connected brushless doubly fed induction

M. Abdelbasset MAHBOUB,Said DRID,M. A. SID,Ridha CHEIKH

《能源前沿（英文）》 2016年 第10卷 第3期   页码 298-307 doi: 10.1007/s11708-016-0411-0

摘要： This paper deals with robust direct power control of a grid-connected brushless doubly-fed induction generator(BDFIG). Using a nonlinear feedback linearization strategy, an attempt is made to improve the desired performances by controlling the generated stator active and reactive power in a linear and decoupled manner. Therefore, to achieve this objective, the Lyapunov approach is used associated with a sliding mode control to guarantee the global asymptotical stability. Thus, an optimal operation of the BDFIG in sub-synchronous operation is obtained as well as the stator power flows with the possibility of keeping stator power factor at a unity. The proposed method is tested with the Matlab/Simulink software. Simulation results illustrate the performances and the feasibility of the designed control.

关键词： brushless doubly fed induction generator (BDFIG)     vector control     Lyapunov theory     power factor unity     active and reactive power    

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Shape design of arch dams under load uncertainties with robust optimization

Fengjie TAN, Tom LAHMER

《结构与土木工程前沿（英文）》 2019年 第13卷 第4期   页码 852-862 doi: 10.1007/s11709-019-0522-x

摘要： Due to an increased need in hydro-electricity, water storage, and flood protection, it is assumed that a series of new dams will be build throughout the world. The focus of this paper is on the non-probabilistic-based design of new arch-type dams by applying means of robust design optimization (RDO). This type of optimization takes into account uncertainties in the loads and in the material properties of the structure. As classical procedures of probabilistic-based optimization under uncertainties, such as RDO and reliability-based design optimization (RBDO), are in general computationally expensive and rely on estimates of the system’s response variance, we will not follow a full-probabilistic approach but work with predefined confidence levels. This leads to a bi-level optimization program where the volume of the dam is optimized under the worst combination of the uncertain parameters. As a result, robust and reliable designs are obtained and the result is independent from any assumptions on stochastic properties of the random variables in the model. The optimization of an arch-type dam is realized here by a robust optimization method under load uncertainty, where hydraulic and thermal loads are considered. The load uncertainty is modeled as an ellipsoidal expression. Comparing with any traditional deterministic optimization method, which only concerns the minimum objective value and offers a solution candidate close to limit-states, the RDO method provides a robust solution against uncertainty. To reduce the computational cost, a ranking strategy and an approximation model are further involved to do a preliminary screening. By this means, the robust design can generate an improved arch dam structure that ensures both safety and serviceability during its lifetime.

关键词： arch dam     shape optimization     robust optimization     load uncertainty     approximation model    

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A hybrid deep learning model for robust prediction of the dimensional accuracy in precision milling of

《机械工程前沿（英文）》 2022年 第17卷 第3期 doi: 10.1007/s11465-022-0688-0

摘要： The use of artificial intelligence to process sensor data and predict the dimensional accuracy of machined parts is of great interest to the manufacturing community and can facilitate the intelligent production of many key engineering components. In this study, we develop a predictive model of the dimensional accuracy for precision milling of thin-walled structural components. The aim is to classify three typical features of a structural component—squares, slots, and holes—into various categories based on their dimensional errors (i.e., “high precision,” “pass,” and “unqualified”). Two different types of classification schemes have been considered in this study: those that perform feature extraction by using the convolutional neural networks and those based on an explicit feature extraction procedure. The classification accuracy of the popular machine learning methods has been evaluated in comparison with the proposed deep learning model. Based on the experimental data collected during the milling experiments, the proposed model proved to be capable of predicting dimensional accuracy using cutting parameters (i.e., “static features”) and cutting-force data (i.e., “dynamic features”). The average classification accuracy obtained using the proposed deep learning model was 9.55% higher than the best machine learning algorithm considered in this paper. Moreover, the robustness of the hybrid model has been studied by considering the white Gaussian and coherent noises. Hence, the proposed hybrid model provides an efficient way of fusing different sources of process data and can be adopted for prediction of the machining quality in noisy environments.

关键词： precision milling     dimensional accuracy     cutting force     convolutional neural networks     coherent noise    

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SinoSCORE: a logistically derived additive prediction model for post-coronary artery bypass grafting

null

《医学前沿（英文）》 2013年 第7卷 第4期   页码 477-485 doi: 10.1007/s11684-013-0284-0

摘要：

This study aims to construct a logistically derived additive score for predicting in-hospital mortality risk in Chinese patients undergoing coronary artery bypass surgery (CABG). Data from 9839 consecutive CABG patients in 43 Chinese centers were collected between 2007 and 2008 from the Chinese Coronary Artery Bypass Grafting Registry. This database was randomly divided into developmental and validation subsets (9:1). The data in the developmental dataset were used to develop the model using logistic regression. Calibration and discrimination characteristics were assessed using the validation dataset. Thresholds were defined for each model to distinguish different risk groups. After excluding 275 patients with incomplete information, the overall mortality rate of the remaining 9564 patients was 2.5%. The SinoSCORE model was constructed based on 11 variables: age, preoperative NYHA stage III or IV, chronic renal failure, extracardiac arteriopathy, chronic obstructive pulmonary disease, preoperative atrial fibrillation or flutter (within 2βweeks), left ventricular ejection fraction, other elective surgery, combined valve procedures, preoperative critical state, and BMI. In the developmental dataset, calibration using a Hosmer-Lemeshow (HL) test was at =β0.44 and discrimination based on the area under the receiver operating characteristic curve (ROC) was 0.80. In the validation dataset, the HL test was at =β0.34 and the area under the ROC (AUC) was 0.78. A logistically derived additive model for predicting in-hospital mortality among Chinese patients undergoing CABG was developed based on the most up-to-date multi-center data from China.

关键词： coronary artery bypass grafting     risk stratification     in-hospital mortality    

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Robust energy-efficient train speed profile optimization in a scenario-based position–time–speed network

《工程管理前沿（英文）》 2021年 第8卷 第4期   页码 595-614 doi: 10.1007/s42524-021-0173-1

摘要： Train speed profile optimization is an efficient approach to reducing energy consumption in urban rail transit systems. Different from most existing studies that assume deterministic parameters as model inputs, this paper proposes a robust energy-efficient train speed profile optimization approach by considering the uncertainty of train modeling parameters. Specifically, we first construct a scenario-based position–time–speed (PTS) network by considering resistance parameters as discrete scenario-based random variables. Then, a percentile reliability model is proposed to generate a robust train speed profile, by which the scenario-based energy consumption is less than the model objective value at α confidence level. To solve the model efficiently, we present several algorithms to eliminate the infeasible nodes and arcs in the PTS network and propose a model reformulation strategy to transform the original model into an equivalent linear programming model. Lastly, on the basis of our field test data collected in Beijing metro Yizhuang line, a series of experiments are conducted to verify the effectiveness of the model and analyze the influences of parameter uncertainties on the generated train speed profile.

关键词： robust train speed profile     percentile reliability model     scenario-based position–time–speed network     mixed-integer programming    

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Multiple target implementation for a doubly fed induction generator based on direct power control under

Heng NIAN,Yi-peng SONG

《信息与电子工程前沿（英文）》 2015年 第16卷 第4期   页码 321-334 doi: 10.1631/FITEE.1400170

摘要： This paper presents a multiple target implementation technique for a doubly fed induction generator (DFIG) under unbalanced and distorted grid voltage based on direct power control (DPC). Based on the mathematical model of DFIG under unbalanced and distorted voltage, the proportional and integral (PI) regulator is adopted to regulate the DFIG average active and reactive powers, while the vector PI (VPI) resonant regulator is used to achieve three alternative control targets: (1) balanced and sinusoidal stator current; (2) smooth instantaneous stator active and reactive powers; (3) smooth electromagnetic torque and instantaneous stator reactive power. The major advantage of the proposed control strategy over the conventional method is that neither negative and harmonic sequence decomposition of grid voltage nor complicated control reference calculation is required. The insensitivity of the proposed control strategy to DFIG parameter deviation is analyzed. Finally, the DFIG experimental system is developed to validate the availability of the proposed DPC strategy under unbalanced and distorted grid voltage.

关键词： Direct power control     Doubly fed induction generator     Unbalanced and distorted grid voltage     Vector proportional and integral resonant regulator     Parameter deviation    

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Understanding the role of nano-TiO on the toxicity of Pb on through modeling–Is it additive or synergistic

《环境科学与工程前沿（英文）》 2022年 第16卷 第5期 doi: 10.1007/s11783-021-1493-4

摘要：

• A two-compartment model is able to quantify the effect of nano-TiO2 on Pb toxicity.

关键词： Algae     C. dubia     Lead     Nano-TiO2     Synergistic toxicity     Two-compartment toxicokinetic-toxicodynamic model    

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Application of fuzzy logic control algorithm as stator power controller of a grid-connected doubly-fed

Ridha CHEIKH, Arezki MENACER, Said DRID, Mourad TIAR

《能源前沿（英文）》 2013年 第7卷 第1期   页码 49-55 doi: 10.1007/s11708-012-0217-7

摘要： This paper discusses the power outputs control of a grid-connected doubly-fed induction generator (DFIG) for a wind power generation systems. The DFIG structure control has a six diode rectifier and a PWM IGBT converter in order to control the power outputs of the DFIG driven by wind turbine. So, to supply commercially the electrical power to the grid without any problems related to power quality, the active and reactive powers ( , ) at the stator side of the DFIG are strictly controlled at a required level, which, in this paper, is realized with an optimized fuzzy logic controller based on the grid flux oriented control, which gives an optimal operation of the DFIG in sub-synchronous region, and the control of the stator power flow with the possibility of keeping stator power factor at a unity.

关键词： doubly-fed induction generator (DFIG)     vector control     fuzzy logic controller     optimization     power factor unity     active and reactive power    

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一种考虑概率分布的鲁棒优化模型

丁然,李歧强,张元鹏

《中国工程科学》 2008年 第10卷 第9期   页码 70-73

摘要：

文章以随机规划中的机会约束思想为指导，根据随机参数的概率分布情况，提出了两种鲁棒性条件约束，并在此基础上建立了一种新的鲁棒优化模型，使模型的可行解控制在一定的鲁棒性指标的范围内。该模型不但可处理约束两端同时含有随机参数的情况，还可以方便地推广到非线性模型中。仿真实例说明了模型的有效性。

关键词： 不确定性     鲁棒优化     随机规划     机会约束    

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Pareto lexicographic α-robust approach and its application in robust multi objective assembly line balancing

null

《机械工程前沿（英文）》 2014年 第9卷 第3期   页码 257-264 doi: 10.1007/s11465-014-0294-x

摘要：

Robustness in most of the literature is associated with min-max or min-max regret criteria. However, these criteria of robustness are conservative and therefore recently new criteria called, lexicographic α-robust method has been introduced in literature which defines the robust solution as a set of solutions whose quality or jth largest cost is not worse than the best possible jth largest cost in all scenarios. These criteria might be significant for robust optimization of single objective optimization problems. However, in real optimization problems, two or more than two conflicting objectives are desired to optimize concurrently and solution of multi objective optimization problems exists in the form of a set of solutions called Pareto solutions and from these solutions it might be difficult to decide which Pareto solution can satisfy min-max, min-max regret or lexicographic α-robust criteria by considering multiple objectives simultaneously. Therefore, lexicographic α-robust method which is a recently introduced method in literature is extended in the current research for Pareto solutions. The proposed method called Pareto lexicographic α-robust approach can define Pareto lexicographic α-robust solutions from different scenarios by considering multiple objectives simultaneously. A simple example and an application of the proposed method on a simple problem of multi objective optimization of simple assembly line balancing problem with task time uncertainty is presented to get their robust solutions. The presented method can be significant to implement on different multi objective robust optimization problems containing uncertainty.

关键词： Pareto     lexicographic α-robust     assembly line balancing    

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基于对齐自修正的鲁棒跨模态检索 Research Article

郭金一1,丁洁玉2

《信息与电子工程前沿（英文）》 2023年 第24卷 第10期   页码 1403-1415 doi: 10.1631/FITEE.2200514

摘要： 跨模态检索通过为不同模态数据建立一致的对齐方式来实现模态间的相互检索。目前多种跨模态检索方法已被提出并取得良好性能。这些方法使用干净对齐的跨模态数据进行训练。虽然这些数据在语义上是匹配的，但相较于互联网上容易获得的噪声对齐的数据（即成对但在语义上不匹配），标注成本很高。当用噪声对齐的数据训练这些模型时，它们的性能会急剧下降。因此，本文提出一种对齐自修正的鲁棒跨模态检索算法（RCAR），显著降低了噪声数据对模型的影响。具体来说，RCAR首先进行多任务学习，减缓模型对噪声数据的过拟合，使数据分离。然后，利用两成分的贝塔混合模型将数据分为干净数据和噪声数据，并根据后验概率修正对齐标签。此外，在噪声对齐范式中定义两种噪声类型：部分噪声数据和完全噪声数据。实验结果表明，与当下流行的跨模态检索方法相比，RCAR在两种类型的噪声下都能取得更稳健的性能。

关键词： 跨模态检索；鲁棒学习；对齐修正；贝塔混合模型    

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Kinematic Model Building and Servo Parameter Identification of 3-HSS Parallel Mechanism

YANG Zhi-yong, WU Jiang, HUANG Tian, NI Yan-bing

《机械工程前沿（英文）》 2006年 第1卷 第1期   页码 60-66 doi: 10.1007/s11465-005-0019-2

摘要：

Aiming at a parallel mechanism with three degrees of freedom, a method for dynamic model building and the parameter identification of its servosystem is presented. First, the reverse solution models of position, velocity, and acceleration of parallelogram branch structure are deduced, and then, its dynamic model of a rigid body is set up by using the virtual work principle. Based on the above model, a method to identify the servo parameter of the parallel mechanism is put up. In this method, the triangle-shaped input with variable frequency is adopted to offset the disadvantages of pseudorandom number sequence in parameter identification, such as dramatically changing the vibration amplitude of the motor, easily impacting the motor that results in its velocity loop to easily open, and so on. Moreover, the rotary inertia can also be identified by the additive mass. The abovementioned data will lay a solid foundation for the optimum performance of the system in the whole workspace.

关键词： building     acceleration     additive     workspace     optimum performance    

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基于内嵌物理信息深度学习模型的增材制造工艺参数及熔池尺寸预测 Article

赵明志, 韦辉亮, 茅仪铭, 张长东, 刘婷婷, 廖文和

《工程（英文）》 2023年 第23卷 第4期   页码 181-195 doi: 10.1016/j.eng.2022.09.015

摘要：

熔池特征对激光粉末床熔融（PBF）的打印质量有显著影响，打印参数和熔池尺寸的定量预测对LPBF中复杂过程的智能控制至关重要。然而由于高度非线性，打印参数和熔池尺寸的双向预测一直极具挑战。为了解决此问题，本工作融合典型实验、机理模型和深度学习研究激光PBF过程中关键参数和熔池特性的正向和逆向预测。实验提供基础数据，机理模型显著增强数据集，多层感知器（MLP）深度学习模型则根据实验和机理模型构建的数据集预测熔池尺寸和工艺参数。结果表明可以实现熔池尺寸和工艺参数的双向预测，最高预测准确率接近99.9%，平均预测准确率超过90.0%。此外，MLP模型的预测准确率与数据集的特征密切相关，即数据集的可学习性对预测准确率有至关重要的影响。通过机理模型增强数据集后的最高预测精度为97.3%，而仅使用实验数据集时的最高预测精度只有68.3%。MLP模型的预测准确率在很大程度上取决于数据集的质量。研究结果表明使用MLP进行复杂相关性的双向预测对于激光PBF是可行的，本工作为选定智能增材制造的工艺条件和结果提供了一个新颖而实用的框架。

关键词： 增材制造     熔池     模型     深度学习     可学习性    

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标题 作者 时间 类型 操作

Long-term exposure to air pollution and cerebrovascular disease: findings from Beijing Health Management Cohort study

期刊论文

Robust control based on the Lyapunov theory of a grid-connected doubly fed induction generator

Ridha CHEIKH, Arezki MENACER, Said DRID

期刊论文

Robust direct power control based on the Lyapunov theory of a grid-connected brushless doubly fed induction

M. Abdelbasset MAHBOUB,Said DRID,M. A. SID,Ridha CHEIKH

期刊论文

Shape design of arch dams under load uncertainties with robust optimization

Fengjie TAN, Tom LAHMER

期刊论文

A hybrid deep learning model for robust prediction of the dimensional accuracy in precision milling of

期刊论文

SinoSCORE: a logistically derived additive prediction model for post-coronary artery bypass grafting

null

期刊论文

Robust energy-efficient train speed profile optimization in a scenario-based position–time–speed network

期刊论文

Multiple target implementation for a doubly fed induction generator based on direct power control under

Heng NIAN,Yi-peng SONG

期刊论文

Understanding the role of nano-TiO on the toxicity of Pb on through modeling–Is it additive or synergistic

期刊论文

Application of fuzzy logic control algorithm as stator power controller of a grid-connected doubly-fed

Ridha CHEIKH, Arezki MENACER, Said DRID, Mourad TIAR

期刊论文

一种考虑概率分布的鲁棒优化模型

丁然,李歧强,张元鹏

期刊论文

Pareto lexicographic α-robust approach and its application in robust multi objective assembly line balancing

null

期刊论文

基于对齐自修正的鲁棒跨模态检索

郭金一1,丁洁玉2

期刊论文

Kinematic Model Building and Servo Parameter Identification of 3-HSS Parallel Mechanism

YANG Zhi-yong, WU Jiang, HUANG Tian, NI Yan-bing

期刊论文

基于内嵌物理信息深度学习模型的增材制造工艺参数及熔池尺寸预测

赵明志, 韦辉亮, 茅仪铭, 张长东, 刘婷婷, 廖文和

期刊论文