浅析数字化在汽车Benchmarking中的应用

竞争车解析对标是汽车Benchmarking的基础工作,现行业竞争车解析对标参数采集均依靠人工作业,工作效率低下。结合业务实践,文章研究了一套自动拍照、自动称重的数字化信息采集系统,通过软硬件结合实现竞争车解析对标参数采集、数据整理、数据传输等全链条业务自动化。该方法的运用可大幅提升整车Benchmarking工作效率,进而缩短产品开发周期,实现效率与效益双提升。

Satellite Derived Geospatial Irrigation Performance Indicators for Benchmarking Studies of Irrigation Systems

Development of irrigation infrastructure and its efficient management is the primary concern for sustainable food production. The assessment of irrigation infrastructure creation, its utilization, diagnostic evaluation of the various performance indices (monitoring) are important to measure the efficiency. Benchmarking of Irrigation Systems (BIS) is for the diagnostic analysis of irrigation performance indicators comprising of Irrigation Infrastructure System (IIS), Agricultural System (AS), Water Delivery Dynamics (WDD). Since, the performance of an irrigation command varies with space and time, utilization of spatial information technologies viz. Remote Sensing (RS), Geographical Information Systems (GIS), Global Positioning Systems (GPS) useful to provide spatial information on several indices in the process of benchmarking (BM). Information requirements for BIS at different stages, utilization of spatial information technologies to derive irrigation performance indicators was discussed with suitable examples and demonstrated in this study. The studies carried out indicates that the geospatial approach for BIS enabled the improvements in data collection methods, diagnostic analysis, spatio-temporal visualisation of BM indicators at disaggregated canal level which would be useful for decision support during the corrective management measures. The conjunctive use of multi-date (medium resolution) satellite data, high spatial resolution data, field data on water deliveries was found to be an alternative to the conventional non-spatial approaches for BIS and thereby better water resources planning and management.

Benchmarking calculations of excitation energies and transition properties with spectroscopic accuracy of highly charged ions used for the fusion plasma and astrophysical plasma

Atomic radiative data such as excitation energies, transition wavelengths, radiative rates, and level lifetimes with high precision are the essential parameters for the abundance analysis, simulation, and diagnostics in fusion and astrophysical plasmas. In this work, we mainly focus on reviewing our two projects performed in the past decade. One is about the ions with Z■30 that are generally of astrophysical interest, and the other one is about the highly charged krypton(Z = 36)and tungsten(Z = 74) ions that are relevant in research of magnetic confinement fusion. Two different and independent methods, namely, multiconfiguration Dirac–Hartree–Fock(MCDHF) and the relativistic many-body perturbation theory(RMBPT) are usually used in our studies. As a complement/extension to our previous works for highly charged tungsten ions with open M-shell and open N-shell, we also mainly focus on presenting and discussing our complete RMBPT and MCDHF calculations for the excitation energies, wavelengths, electric dipole(E1), magnetic dipole(M1), electric quadrupole(E2), and magnetic quadrupole(M2) transition properties, and level lifetimes for the lowest 148 levels belonging to the 3l3configurations in Al-like W61+. We also summarize the uncertainties of our systematical theoretical calculations, by cross-checking/validating our datasets from our RMBPT and MCDHF calculations, and by detailed comparisons with available accurate observations and other theoretical calculations. The data are openly available in Science Data Bank at https://doi.org/10.57760/sciencedb.10569.

Medium-term Air Quality Benchmarking for Ecosystem Monitoring and Sustainability Planning: Case Study Dallas County (U.S.A.) 2015 to 2020

Medium-term air quality assessment,benchmarking it to recent past data can usefully complement short-term air quality index data for monitoring purposes.By using daily and monthly averaged data,medium-term air quality benchmarking provides a distinctive perspective with which to monitor air quality for sustainability planning and ecosystem perspectives.By normalizing the data for individual air pollutants to a standard scale they can be more easily integrated to generate a daily combined local area benchmark(CLAB).The objectives of the study are to demonstrate that medium-term air quality benchmarking can be tailored to reflect local conditions by selecting the most relevant pollutants to incorporate in the CLAB indicator.Such a benchmark can provide an overall air quality assessment for areas of interest.A case study is presented for Dallas County(U.S.A.)applying the proposed method by benchmarking 2020 data for air pollutants to their trends established for 2015 to 2019.Six air pollutants considered are:ozone,carbon monoxide,nitrogen dioxide,sulfur dioxide,benzene and particulate matter less than 2.5 micrometres.These pollutants are assessed individually and in terms of CLAB,and their 2020 variations for Dallas County compared to daily trends established for years 2015 to 2019.Reductions in benzene and carbon monoxide during much of 2020 are clearly discernible compared to preceding years.The CLAB indicator shows clear seasonal trends for air quality for 2015 to 2019 with high pollution in winter and spring compared to other seasons that is strongly influenced by climatic variations with some anthropogenic inputs.Conducting CLAB analysis on an ongoing basis,using a relevant near-past time interval for benchmarking that covers several years,can reveal useful monthly,seasonal and annual trends in overall air quality.This type of medium-term,benchmarked air quality data analysis is well suited for ecosystem monitoring.

生存进化阶段性搜索微粒群算法及其可靠性冗余分配优化应用

为高效解决含有异质冗余的多态系统(MSS)可靠性优化问题,并弥补微粒群优化(PSO)算法易早熟收敛的不足,从作用力方式和种群拓扑结构两方面对算法进行改进。改进PSO算法中单一的作用力方式,设置前后两个搜索阶段,对应两个搜索阶段分别构造平衡引斥力方式和双层引力(个体和全局最优解引力、中间适应度微粒引力)方式,提出阶段性搜索微粒群(SPSO)算法;利用生物个体“择友而交”和优胜劣汰的生存体系构建生存进化(SE)拓扑结构,以结构演化和算法进化并行方式将该拓扑结构融入SPSO算法,提出生存进化阶段性搜索微粒群(SPSO-SE)算法,进一步提升算法的优化性能;利用Benchmark函数对所提算法与PSO的改进算法进行测试对比,结果表明,所提SPSO-SE算法具有更好的寻优能力。采用SPSO-SE算法对串-并联和桥式结构的多态系统的可靠性冗余分配问题进行优化,得到的系统结构费用更低、可靠度更高。

基于谱元法和北方苍鹰算法的振动损伤检测

【目的】为了解决结构损伤检测中有限元法建模不精确和计算成本高的问题,提出了一种结合谱元法与北方苍鹰优化算法(NGO)的结构健康监测(SHM)技术。【方法】首先,采用谱元法建立结构的频响函数,并应用于结构的损伤定位与损伤检测目标函数的构造,将损伤检测划分为两阶段问题,以降低算法优化维度和检测复杂性。其次,引入北方苍鹰优化算法(NGO),对目标函数进行优化求解。最后,以平面桁架结构和ASCE Benchmark结构为研究对象,利用NGO、粒子群优化(PSO)和蚁狮优化(ALO)算法对其各种损伤工况进行损伤检测性能对比。【结果】结果表明,在低维度和简单结构中,NGO,PSO和ALO算法均表现出良好的求解能力;但在高维度和大型复杂结构中,NGO相较于PSO和ALO算法具有更高的损伤检测能力和鲁棒性。【结论】改进后的方法提高了损伤检测数值建模的精度。

Benchmarking技术在汽车开发领域中的应用

介绍了Benchmarking技术的概念;综合国内外汽车发展的历史和现状,针对我国汽车开发经验、知识积累不足问题,引入了Benchmarking技术的样车分析技术体系,细化了样车Benchmarking的流程,说明了Benchmarking技术的应用过程。最后介绍了目前Benchmarking技术在汽车开发知识库系统中的应用现状。

通智测试——基于动态具身物理社会交互环境的通用人工智能测试

The release of the generative pre-trained transformer(GPT)series has brought artificial general intelligence(AGI)to the forefront of the artificial intelligence(AI)field once again.However,the questions of how to define and evaluate AGI remain unclear.This perspective article proposes that the evaluation of AGI should be rooted in dynamic embodied physical and social interactions(DEPSI).More specifically,we propose five critical characteristics to be considered as AGI benchmarks and suggest the Tong test as an AGI evaluation system.The Tong test describes a value-and ability-oriented testing system that delineates five levels of AGI milestones through a virtual environment with DEPSI,allowing for infinite task generation.We contrast the Tong test with classical AI testing systems in terms of various aspects and propose a systematic evaluation system to promote standardized,quantitative,and objective benchmarks and evaluation of AGI.

竖向地震作用下层间隔震结构的动力反应研究

文章针对竖向地震作用下高层结构隔震层位置变化对结构竖向动力反应的影响问题,研究5种层间隔震结构分别在3种竖向地震作用下的竖向动力反应。以国际平台的20层Benchmark钢结构模型为基准模型,利用ANSYS软件建立隔振层分别位于第1层、第3层、第5层、第7层和第9层的层间隔震结构有限元数值模型,对比分析5种层间隔震结构分别在竖向ElCentro波、竖向Taft波、竖向天津波作用下的楼层竖向位移、楼层位移角、楼层竖向加速度和基底轴力等竖向动力反应。结果表明:在竖向地震作用下,楼层竖向位移和楼层位移角控制效果较差,甚至会出现增大的现象,基底轴力具有较小的控制效果;随着隔震层位置的升高,楼层竖向加速度和基底轴力均逐渐增大,但当隔震层位于第9层时,楼层竖向加速度和基底轴力相较于隔震层位于第7层时有一定的减小。该文研究成果可用于考虑竖向地震作用的高层结构抗震设计。

Benchmarking：竞争情报的一种重要手段

Ｂｅｎｃｈｍａｒｋｉｎｇ的有关内容是竞争情报的重要组成部分。Ｂｅｎｃｈｍａｒｋｉｎｇ的理论和方法是随着竞争情报的发展而发展起来的。本文从Ｂｅｎｃｈｍａｒｋｉｎｇ的由来、基本概念、种类等步骤方面较为全面地论述了Ｂｅｎｃｈｍａｒｋｉｎｇ的有关情况，希望能引起对Ｂｅｎｃｈｍａｒｋｉｎｇ这一竞争情报重要手段研究的重视。

SDFPB在九层Benchmark钢框架中的隔震性能研究

为研究SMA-复摩擦摆支座(Shape Memory Alloys Double Friction Pendulum Bearing,SDFPB)在多、高层建筑结构中的隔震性能和安全性,基于OpenSees建立了SDFPB的有限元模型,分析了SDFPB力学性能影响因素,将其应用于九层Benchmark钢框架结构中,对比了隔震结构和非隔震结构的地震响应。研究表明,SDFPB隔震系统可以改善九层Benchmark钢框架动力特性,显著削弱上部结构在地震作用下的楼层加速度、层间位移角和层间剪力,有效控制隔震层位移,在多、高层建筑结构中可发挥良好隔震效果并提升安全性。

用Benchmarking方法分析我校信息管理与信息系统专业建设及发展

本文针对我校信息管理专业的实际情况,以上海交大作为比较对象,用Benchmarking方法从人才培养、管理科学、社会服务等方面作为比较内容,提出赶超对策和实施计划,最后总结了文中的不足。

NoSQL数据库实践教学:结合Benchmarking的方法

随着大数据、人工智能时代的到来,NoSQL数据库对工业界和学术界的影响也愈加深入,如何培养学生的NoSQL实践应用能力成为关键问题。但是,受限于学分设定、实验环境等,当前高校对于相关课程的开设和教学力度不够,学生缺少相关的NoSQL数据库实践能力,与业界所需大数据能力的鸿沟越拉越大。针对该问题,介绍所在团队在过去5年中,基于双层学习模式开展NoSQL数据库实践教学的经验。结合Benchmarking方法,根据学生的课程评价和反馈,验证了该教学模式取得了较好的实践教学效果。

超越自我：Benchmarking的再研究

Benchmarking在英文中的原义是“板凳标尺”，中文有的译作“定标赶超”，“标尺”等，还有译为形象化的“见贤思齐”。实际上它是一种企业管理的工具，即“学习、复制、创新”的过程。对于Benchmarking，有多种说法。

Synergistic Swarm Optimization Algorithm

This research paper presents a novel optimization method called the Synergistic Swarm Optimization Algorithm(SSOA).The SSOA combines the principles of swarmintelligence and synergistic cooperation to search for optimal solutions efficiently.A synergistic cooperation mechanism is employed,where particles exchange information and learn from each other to improve their search behaviors.This cooperation enhances the exploitation of promising regions in the search space while maintaining exploration capabilities.Furthermore,adaptive mechanisms,such as dynamic parameter adjustment and diversification strategies,are incorporated to balance exploration and exploitation.By leveraging the collaborative nature of swarm intelligence and integrating synergistic cooperation,the SSOAmethod aims to achieve superior convergence speed and solution quality performance compared to other optimization algorithms.The effectiveness of the proposed SSOA is investigated in solving the 23 benchmark functions and various engineering design problems.The experimental results highlight the effectiveness and potential of the SSOA method in addressing challenging optimization problems,making it a promising tool for a wide range of applications in engineering and beyond.Matlab codes of SSOA are available at:https://www.mathworks.com/matlabcentral/fileexchange/153466-synergistic-swarm-optimization-algorithm.

Multiobjective Differential Evolution for Higher-Dimensional Multimodal Multiobjective Optimization

In multimodal multiobjective optimization problems(MMOPs),there are several Pareto optimal solutions corre-sponding to the identical objective vector.This paper proposes a new differential evolution algorithm to solve MMOPs with higher-dimensional decision variables.Due to the increase in the dimensions of decision variables in real-world MMOPs,it is diffi-cult for current multimodal multiobjective optimization evolu-tionary algorithms(MMOEAs)to find multiple Pareto optimal solutions.The proposed algorithm adopts a dual-population framework and an improved environmental selection method.It utilizes a convergence archive to help the first population improve the quality of solutions.The improved environmental selection method enables the other population to search the remaining decision space and reserve more Pareto optimal solutions through the information of the first population.The combination of these two strategies helps to effectively balance and enhance conver-gence and diversity performance.In addition,to study the per-formance of the proposed algorithm,a novel set of multimodal multiobjective optimization test functions with extensible decision variables is designed.The proposed MMOEA is certified to be effective through comparison with six state-of-the-art MMOEAs on the test functions.

A survey on multi-agent reinforcement learning and its application

Multi-agent reinforcement learning(MARL)has been a rapidly evolving field.This paper presents a comprehensive survey of MARL and its applications.We trace the historical evolution of MARL,highlight its progress,and discuss related survey works.Then,we review the existing works addressing inherent challenges and those focusing on diverse applications.Some representative stochastic games,MARL means,spatial forms of MARL,and task classification are revisited.We then conduct an in-depth exploration of a variety of challenges encountered in MARL applications.We also address critical operational aspects,such as hyperparameter tuning and computational complexity,which are pivotal in practical implementations of MARL.Afterward,we make a thorough overview of the applications of MARL to intelligent machines and devices,chemical engineering,biotechnology,healthcare,and societal issues,which highlights the extensive potential and relevance of MARL within both current and future technological contexts.Our survey also encompasses a detailed examination of benchmark environments used in MARL research,which are instrumental in evaluating MARL algorithms and demonstrate the adaptability of MARL to diverse application scenarios.In the end,we give our prospect for MARL and discuss their related techniques and potential future applications.

Analysis for integrated energy system:Benchmarking methods and implementation

The selection of suitable models and solutions is a fundamental requirement for con-ducting energy flow analysis in integrated energy systems(IES).However,this task is challenging due to the vast number of existing models and solutions,making it difficult to comprehensively compare scholars'studies with current work.In this paper,we aim to address this issue by presenting a comprehensive overview of mainstream IES models and clarifying their relationships,thereby providing guidance for scholars in selecting appro-priate models.Additionally,we introduce several widely used solvers for solving algebraic and differential equations,along with their detailed implementations in the energy flow analysis of IES.Furthermore,we conduct extensive testing and demonstration of these models and methods in various cases to establish benchmarking datasets.To facilitate reproducibility,verification and comparisons,we provide open‐source access to these datasets,including system data,analysis settings and implementations of the various solvers in the mainstream models.Scholars can utilise the provided datasets to reproduce the results,verify the findings and perform comparative analyses.Moreover,they have the flexibility to customise these settings according to their specific requirements.

TLCD-基础隔震结构混合控制抗风性能研究

文章探讨了基础隔震技术结合调谐液体阻尼器(TLCD)对高层建筑抗风性能的提升研究。基础隔震技术虽然可以显著减少地震对上部结构的破坏,但可能增加建筑对风的敏感性。TLCD因其经济性和适用性,尤其适用于基础隔震结构。建立了20层Benchmark模型,并对比分析了仅采用基础隔震与采用基础隔震+TLCD混合控制的风致响应。结果表明,混合控制方案可以显著减小结构位移和加速度,顶层加速度降低约30%,有效增强了基础隔震建筑的抗风性能和居住舒适性。这项研究为高层隔震建筑的风振控制提供了创新的设计理念和实用方法,具有重要的参考价值。