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An optimization-based method for prediction of lumbar spine segmental kinematics from the measurements of thorax and pelvic kinematics

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INTERNATIONAL JOURNAL FOR NUMERICAL methodS IN BIOMEDICAL ENGINEERING 2015年第12期31卷 2015 Dec;31(12)页

作者： Shojaei, I. Arjmand, N. Bazrgari, B. Univ Kentucky Dept Biomed Engn Lexington KY 40506 USA Sharif Univ Technol Dept Mech Engn Tehran Iran

Given measurement difficulties, earlier modeling studies have often used some constant ratios to predict lumbar segmental kinematics from measurements of total lumbar kinematics. Recent imaging studies suggested distribution of lumbar kinematics across its vertebrae changes with trunk rotation, lumbar posture, and presence of load. An optimization-based method is presented and validated in this study to predict segmental kinematics from measured total lumbar kinematics. Specifically, a kinematics-driven biomechanical model of the spine is used in a heuristic optimization procedure to obtain a set of segmental kinematics that, when prescribed to the model, were associated with the minimum value for the sum of squared predicted muscle stresses across all the lower back muscles. Furthermore, spinal loads estimated using the predicted kinematics by the present method were compared with those estimated using constant ratios. Predicted segmental kinematics were in good agreement with those obtained by imaging with an average error of similar to 10%. Compared with those obtained using constant ratios, predicted spinal loads using segmental kinematics obtained here were in general smaller. In conclusion, the proposed method offers an alternative tool for improving model-based estimates of spinal loads where image-based measurement of lumbar kinematics is not feasible. Copyright (C) 2015 John Wiley & Sons, Ltd.

关键词： optimization-based method lumbar spine kinematics-driven method spinal loads

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Integrated multiresolution framework for spatialized population synthesis

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TRANSPORTATION 2024年第3期51卷 823-852页

作者： Khachman, Mohamed Morency, Catherine Ciari, Francesco Polytech Montreal Dept Civil Geol & Min Engn CP 6079 Montreal PQ H3C 3A7 Canada

Large-scale agent-based microsimulation platforms, increasingly used in transportation demand modelling, require fully enumerated and spatialized lists of the population and its sociodemographic characteristics as input. The quality of the synthetic population, measured as its ability to reproduce the sociodemographic characteristics of the real population and their spatial distributions, is thus a determinant factor of the model reliability. While many efforts were devoted to improving the sociodemographic accuracy of synthetic populations, less attention was paid to perfecting their spatial precision. Conventional spatialized population synthesis methods, where the generation and spatialization processes are separated, are vulnerable to inconsistencies between zonal synthetic populations, and the built environments on which they are then distributed. These methods also present transferability issues that lie in their high reliance on rich spatialized datasets and knowledge of the local context. Hence, we propose an integrated multiresolution framework (IMF) that overcomes the limitations of the conventional framework (CF) by its ability to directly generate synthetic populations at the building resolution with minimal data requirements. The IMF includes an extension of an optimization-based method to multiresolution applications where any number and aggregation of spatial resolutions can efficiently be controlled. The CF and the IMF are applied to generate synthetic populations for Montreal, Canada. We define and measure sociodemographic accuracy, spatial precision, overall quality, and building-resolution fit of the synthetic populations to compare the frameworks' performances. Despite a small loss in accuracy, the IMF achieves drastically better spatial precision, overall quality and building-resolution fit of synthetic populations, compared to the CF.

关键词： Population synthesis Spatial disaggregation Integrated framework Multiresolution control optimization-based method Travel demand modelling

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optimization-based transient control of turbofan engines: a sequential quadratic programming approach

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INTERNATIONAL JOURNAL OF TURBO & JET-ENGINES 2024年第Sup1期40卷 s119-s128页

作者： Wang, Jiqiang Hu, Huan Zhang, Weicun Hu, Zhongzhi Chinese Acad Sci Ningbo Inst Mat Technol & Engn Room 507Bldg IAMT South1219 Zhongguan West Rd Ningbo 315201 Peoples R China Aerofugia Technol Chengdu Co LTD High Tech Zone 200 Tianfu 5th St Chengdu 610093 Peoples R China Univ Sci & Technol Beijing Sch Automat Sci & Elect Engn Beijing 100083 Peoples R China Tsinghua Univ Inst Aero Engine Beijing 100084 Peoples R China

Engine transient control has been challenging due to its stringent requirements from both performance and safety. Many methodologies have been proposed such as conventional schedule-based methods, linear parameter varying, multiobjective optimization and evolutionary computations etc. These approaches have been well-established and led to a series of significant results. However, they are either not providing limit protection or requiring exhaustive computational resources, particularly when generating results into full flight envelope applications. Consequently a compromise between limit protection and computational complexity is necessitated. This note considers a sequential quadratic programming (SQP)-based method for full flight envelope investigations. The proposed method can provide important design guidance and the corresponding claims are validated through detailed analysis and simulations.

关键词： engine transient control limit protection control optimization-based method SQP approach

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Cost-Driven Screening of Network Constraints for the Unit Commitment Problem

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IEEE TRANSACTIONS ON POWER SYSTEMS 2023年第1期38卷 42-51页

作者： Porras, Alvaro Pineda, Salvador Morales, Juan Miguel Jimenez-Cordero, Asuncion Univ Malaga OASYS Res Grp Malaga 29071 Spain

In an attempt to speed up the solution of the unit commitment (UC) problem, both machine-learning and optimization-based methods have been proposed to lighten the full UC formulation by removing as many superfluous line-flow constraints as possible. While the elimination strategies based on machine learning are fast and typically delete more constraints, they may be over-optimistic and result in infeasible UC solutions. For their part, optimization-based methods seek to identify redundant constraints in the full UC formulation by exploring the feasibility region of an LP-relaxation. In doing so, these methods only get rid of line-flow constraints whose removal leaves the feasibility region of the original UC problem unchanged. In this paper, we propose a procedure to substantially increase the line-flow constraints that are filtered out by optimization-based methods without jeopardizing their appealing ability of preserving feasibility. Our approach is based on tightening the LP-relaxation that the optimization-based method uses with a valid inequality related to the objective function of the UC problem and hence, of an economic nature. The result is that the so strengthened optimization-based method identifies not only redundant line-flow constraints but also inactive ones, thus leading to more reduced UC formulations.

关键词： Costs Power transmission lines Machine learning Technological innovation Schedules Production optimization Bounding constraint screening cost-driven approach optimization-based method unit commitment

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Transitivity analysis of preference relations under the impact of indifferent voters

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GRANULAR COMPUTING 2023年第6期8卷 1451-1466页

作者： Liu, Fang Qiu, Mei-Yu Zhou, Da-Hai Guangxi Univ Sch Math & Informat Sci 100 Daxue Rd Nanning 530004 Guangxi Peoples R China

Voting is a common way to reach consensus between decision makers with incompatible opinions in a practical situation. Under the situation with indifferent voters, the pairwise comparison matrix originating from a voting profile could be determined as a preference relation without additively reciprocal property, which is recalled additive non-reciprocal preference relations (ANrPRs). In this paper, some transitivity properties of ANrPRs are addressed involving additive transitivity, weak transitivity, moderate transitivity, and strong transitivity. The considered transitivity properties of ANrPRs are measured by constructing a quantification index. The simple majority rule and a novel optimization-based method are proposed to determine the winner. It is observed that the transitivity properties of ANrPRs are closely related to the occurrence of some voting paradoxes.

关键词： Transitivity analysis Additive non-reciprocal preference relation (ANrPR) Voting paradox optimization-based method

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optimization-based Energy Management Strategy for Hybrid Electric Tramways 22

Optimization-based Energy Management Strategy for Hybrid Ele...

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22nd International Conference on Control, Automation and Systems (ICCAS)

作者： Truong, H. V. A. Trinh, H. A. Ahn, K. K. Univ Ulsan Dept Mech & Automot Engn Ulsan 44610 South Korea

ISBN: (纸本)9788993215243

This paper presents a novel real-time optimization-based (RTOB) EMS with high-level and low-level controls for hybrid electric tramways (HETs). The RTOB methodology is constructed based on a modified extremum seeking (ES) for the HET powered by a proton membrane exchange fuel cell (PEMFC), battery, and supercapacitors (SCs). In this configuration, new equivalent state-of-charge and adaptive co-state are introduced the suggested strategy implementation. To verify the effectiveness of the proposed algorithm, numerical simulations are carried out and compared between the suggested strategy with fuzzy-based EMS and equivalent consumption minimization strategy (ECMS) in stabilizing energy storage devices (ESDs) SOC.

关键词： PEM fuel cell Hybrid power source Energy management strategy Extremum seeking optimization-based method

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optimization-based model order reduction of fluid-structure interaction problems

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JOURNAL OF COMPUTATIONAL PHYSICS 2025年 536卷

作者： Taddei, Tommaso Xu, Xuejun Zhang, Lei Univ Bordeaux IMB UMR 5251 F-33400 Talence France Inria Bordeaux Sud Ouest Team MEMPHIS F-33400 Talence France Tongji Univ Sch Math Sci Key Lab Intelligent Comp & Applicat Minist Educ Shanghai 200092 Peoples R China Chinese Acad Sci AMSS Inst Computat Math Beijing 100190 Peoples R China

We introduce optimization-based full-order and reduced-order formulations of fluid-structure interaction problems. We study the flow of an incompressible Newtonian fluid which interacts with an elastic body: we consider an arbitrary Lagrangian Eulerian formulation of the fluid problem and a fully Lagrangian formulation of the solid problem;we rely on a finite element discretization of both fluid and solid equations. The distinctive feature of our approach is an implicit coupling of fluid and structural problems that relies on the solution to a constrained optimization problem with equality constraints. We discuss the application of projection-based model reduction to both fluid and solid subproblems: we rely on Galerkin projection for the solid equations and on least-squares Petrov-Galerkin projection for the fluid equations. Numerical results for three model problems illustrate the many features of the formulation.

关键词： Model order reduction Fluid-structure interaction Partitioned method optimization-based method

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UNTARGETED ADVERSARIAL ATTACK VIA EXPANDING THE SEMANTIC GAP

UNTARGETED ADVERSARIAL ATTACK VIA EXPANDING THE SEMANTIC GAP

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Wu, Aming Han, Yahong Zhang, Quanxin Kuang, Xiaohui Tianjin Univ Coll Intelligence & Comp Tianjin Peoples R China Beijing Inst Technol Beijing Peoples R China Natl Key Lab Sci & Technol Informat Syst Secur Beijing Peoples R China

ISBN: (纸本)9781538695524

Recent studies have demonstrated deep neural network-based image classifiers are vulnerable to adversarial examples. Although many existing methods could obtain outstanding attack performance, they often require certain information about the attacked model, e.g., the output category scores. Meanwhile, the optimization-based methods need many steps to generate adversarial examples. In practice, we could obtain the output label but the category scores. Besides, compared to those samples with large semantic category gaps, e.g., Panda and Gibbon, most existing methods are not easy to find adversarial examples on samples with small semantic category gaps, e.g., Tabby Cat and Egyptian Cat. Thus, we propose an untargeted adversarial attack method via expanding the semantic gap, which only relies on the output label. And we use the optimization-based method to generate adversarial examples. On five normally trained models and five state-of-the-art attack methods, extensive experiments show that our method is effective and obtains better attack performance.

关键词： Adversarial example semantic gap optimization-based method

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Regional bivariate modeling of droughts using L-comoments and copulas

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STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT 2017年第5期31卷 1199-1210页

作者： Abdi, Amin Hassanzadeh, Yousef Talatahari, Siamak Fakheri-Fard, Ahmad Mirabbasi, Rasoul Univ Tabriz Dept Civil Engn Tabriz Iran Univ Tabriz Dept Agr Engn Tabriz Iran Shahrekord Univ Dept Water Engn Shahrekord Iran

The regional bivariate modeling of drought characteristics using the copulas provides valuable information for water resources management and drought risk assessment. The regional frequency analysis (RFA) can specify the similar sites within a region using L-comoments approach. One of the important steps in the RFA is estimating regional parameters of the copula function. In the present study, an optimization-based method along with the adjusted charged system search are introduced and applied to estimate the regional parameters of the copula models. The capability of the proposed methodology is illustrated by copula functions on drought events. Three commonly used copulas containing Clayton, Frank and Gumbel are employed to derive the joint distribution of drought severity and duration. The result of the new method are compared to the method of moments and after applying several goodness-of-fit tests, the results indicate that the new method provides higher accuracy than the classic one. Furthermore, the results of the upper tail dependence coefficient indicate that the Gumbel copula is the best-fitted copula among the other ones for modeling drought characteristics.

关键词： Drought Bivariate analysis L-comoments approach optimization-based method Copula function Adjusted charged system search

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A new collision avoidance model for pedestrian dynamics

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Chinese Physics B 2015年第3期24卷 453-462页

作者：王千龄陈姚董海荣周敏宁滨 State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University School of Electronic and Information Engineering Beijing Jiaotong University

The pedestrians can only avoid collisions passively under the action of forces during simulations using the social force model, which may lead to unnatural behaviors. This paper proposes an optimization-based model for the avoidance of collisions, where the social repulsive force is removed in favor of a search for the quickest path to destination in the pedestrian＇s vision field. In this way, the behaviors of pedestrians are governed by changing their desired walking direction and desired speed. By combining the critical factors of pedestrian movement, such as positions of the exit and obstacles and velocities of the neighbors, the choice of desired velocity has been rendered to a discrete optimization problem. Therefore,it is the self-driven force that leads pedestrians to a free path rather than the repulsive force, which means the pedestrians can actively avoid collisions. The new model is verified by comparing with the fundamental diagram and actual data. The simulation results of individual avoidance trajectories and crowd avoidance behaviors demonstrate the reasonability of the proposed model.

关键词： pedestrian dynamics social force model collision avoidance optimization-based method

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