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FL-FN-MOGA Based Traffic Signal Control

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Journal of Systems engineering and Electronics 2003年第3期14卷 14-23页

作者： Wei Wu & zhang Yi department of automation, Tsinghua university, Beijing 100084, P. R. china department of automation Tsinghua University Beijing 100084 P. R. China

In this paper, a traffic signal control method based on fuzzy logic (FL), fuzzy-neuro (FN) and multi-objective genetic algorithms (MOGA) for an isolated four-approach intersection with through and left-turning movements is presented. This method has an adaptive signal timing ability, and can make adjustments to signal timing in response to observed *** 'urgency degree' term, which can describe the different user's demand for green time is used in decision-making by which strategy of signal timing can be determined. Using a fuzzy logic controller, we can determine whether to extend or terminate the current signal phase and select the sequences of phases. In this paper, a method based on fuzzy-neuro can be used to predict traffic parameters used in fuzzy logic controller. The feasibility of using a multi-objective genetic algorithm ( MOGA) to find a group of optimizing sets of parameters for fuzzy logic controller depending on different objects is also demonstrated. Simulation results show that the proposed methed is effecfive to adjust the signal timing in response to changing traffic conditions on a real-time basis, and the controller can produce lower vehicle delays and percentage of stopped vehicles than a traffic-actuated controller.

关键词： Traffic signal control Fuzzy logic Fuzzy-neuro Multi-objective genetic algorithms.

Hybrid modeling for carbon monoxide gas-phase catalytic coupling to synthesize dimethyl oxalate process

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Chinese Journal of Chemical engineering 2024年第6期70卷 234-250页

作者： Shida Gao Cuimei Bo Chao Jiang Quanling zhang Genke Yang Jian Chu Ningbo Artificial Intelligence Institute Shanghai Jiao Tong UniversityNingbo 315012China department of automation Shanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of Industrial Internet+Safety Production of Hazardous Chemical Ministry of Emergency ManagementNanjing Tech UniversityNanjing 211816China

Ethylene glycol(EG)plays a pivotal role as a primary raw material in the polyester industry,and the syngas-to-EG route has become a significant technical route in *** carbon monoxide(CO)gas-phase catalytic coupling to synthesize dimethyl oxalate(DMO)is a crucial process in the syngas-to-EG route,whereby the composition of the reactor outlet exerts influence on the ultimate quality of the EG product and the energy consumption during the subsequent separation ***,measuring product quality in real time or establishing accurate dynamic mechanism models is *** effectively model the DMO synthesis process,this study proposes a hybrid modeling strategy that integrates process mechanisms and data-driven *** CO gas-phase catalytic coupling mechanism model is developed based on intrinsic kinetics and material balance,while a long short-term memory(LSTM)neural network is employed to predict the macroscopic reaction rate by leveraging temporal relationships derived from archived *** proposed model is trained semi-supervised to accommodate limited-label data scenarios,leveraging historical *** integrating these predictions with the mechanism model,the hybrid modeling approach provides reliable and interpretable forecasts of mass *** investigations unequivocally validate the superiority of the proposed hybrid modeling approach over conventional data-driven models(DDMs)and other hybrid modeling techniques.

关键词： Carbon monoxide Dynamic modeling Hybrid model Reaction kinetics Semi-supervised learning

Enhancing Evolutionary Algorithms With Pattern Mining for Sparse Large-Scale Multi-Objective Optimization Problems

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IEEE/CAA Journal of Automatica Sinica 2024年第8期11卷 1786-1801页

作者： Sheng Qi Rui Wang Tao zhang Weixiong Huang Fan Yu Ling Wang College of Systems engineering National University of Defense TechnologyChangsha 410073China College of Systems engineering National University of Defense TechnologyChangsha 410073and also with the Xiangjiang LaboratoryChangsha 410205China College of Transportation and engineering Central South UniversityChangsha 410073China department of automation Tsinghua UniversityBeijing 100084China

Sparse large-scale multi-objective optimization problems(SLMOPs)are common in science and ***,the large-scale problem represents the high dimensionality of the decision space,requiring algorithms to traverse vast expanse with limited computational ***,in the context of sparse,most variables in Pareto optimal solutions are zero,making it difficult for algorithms to identify non-zero variables *** paper is dedicated to addressing the challenges posed by *** start,we introduce innovative objective functions customized to mine maximum and minimum candidate *** substantial enhancement dramatically improves the efficacy of frequent pattern *** this way,selecting candidate sets is no longer based on the quantity of nonzero variables they contain but on a higher proportion of nonzero variables within specific ***,we unveil a novel approach to association rule mining,which delves into the intricate relationships between non-zero *** novel methodology aids in identifying sparse distributions that can potentially expedite reductions in the objective function *** extensively tested our algorithm across eight benchmark problems and four real-world *** results demonstrate that our approach achieves competitive solutions across various challenges.

关键词： Evolutionary algorithms pattern mining sparse large-scale multi-objective problems(SLMOPs) sparse large-scale optimization.

Large circuit models: opportunities and challenges

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Science china(Information Sciences) 2024年第10期67卷 25-66页

作者： Lei CHEN Yiqi CHEN zhufei CHU wenji FANG Tsung-Yi HO Ru HUANG Yu HUANG Sadaf KHAN Min LI Xingquan LI Yu LI Yun LIANG Jinwei LIU Yi LIU Yibo LIN Guojie LUO Hongyang PAN Zhengyuan SHI Guangyu SUN Dimitrios TSARAS Runsheng WANG Ziyi WANG Xinming WEI zhiyao XIE Qiang xu Chenhao xuE Junchi YAN Jun YANG Bei YU Mingxuan YUAN Evangeline F.Y.YOUNG xuan ZENG Haoyi zhang Zuodong zhang Yuxiang ZHAO Hui-Ling ZHEN Ziyang ZHENG Binwu zhu Keren zhu Sunan ZOU Huawei Noah’s Ark Lab School of Integrated Circuits Peking University Faculty of Electrical engineering and Computer Science Ningbo University department of Electronic and Computer engineering Hong Kong University of Science and Technology department of Computer Science and engineering The Chinese University of Hong Kong School of Integrated Circuits Southeast University Huawei HiSilicon Peng Cheng Laboratory School of Computer Science Peking University School of Microelectronics State Key Laboratory of Integrated Chips and System Fudan University School of Artificial Intelligence Shanghai Jiao Tong University

Within the electronic design automation(EDA) domain, artificial intelligence(AI)-driven solutions have emerged as formidable tools, yet they typically augment rather than redefine existing methodologies. These solutions often repurpose deep learning models from other domains, such as vision, text, and graph analytics, applying them to circuit design without tailoring to the unique complexities of electronic circuits. Such an “AI4EDA” approach falls short of achieving a holistic design synthesis and understanding,overlooking the intricate interplay of electrical, logical, and physical facets of circuit data. This study argues for a paradigm shift from AI4EDA towards AI-rooted EDA from the ground up, integrating AI at the core of the design process. Pivotal to this vision is the development of a multimodal circuit representation learning technique, poised to provide a comprehensive understanding by harmonizing and extracting insights from varied data sources, such as functional specifications, register-transfer level(RTL) designs, circuit netlists,and physical layouts. We champion the creation of large circuit models(LCMs) that are inherently multimodal, crafted to decode and express the rich semantics and structures of circuit data, thus fostering more resilient, efficient, and inventive design methodologies. Embracing this AI-rooted philosophy, we foresee a trajectory that transcends the current innovation plateau in EDA, igniting a profound “shift-left” in electronic design methodology. The envisioned advancements herald not just an evolution of existing EDA tools but a revolution, giving rise to novel instruments of design-tools that promise to radically enhance design productivity and inaugurate a new epoch where the optimization of circuit performance, power, and area(PPA) is achieved not incrementally, but through leaps that redefine the benchmarks of electronic systems' capabilities.

关键词： AI-rooted EDA large circuit models (LCMs) multimodal circuit representation learning circuit optimization

Comparative study on the hydrogen storage performance of as-milled MgRENi rapid quenched alloy catalyzed by metal sulfides

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Journal of Magnesium and Alloys 2024年第5期12卷 2010-2023页

作者： Xiaoping Dong Zhaoqing zhang Liying Yang Shenghai Xin Dandan Su zhiyuan Li department of Mechanical Design and Manufacture and automation Hebei UniversityBaoding 071000PR China Baoding New Energy Vehicle Power engineering Technology Research Center Hebei UniversityBaoding 071002PR China Hebei Technology Innovation Center for Lightweight of New Energy Vehicle Power System(Preparation) Hebei UniversityBaoding 071002PR China

The composites of Mg_(20)Pr_(1)Sm_(3)Y_(1)Ni_(10)as-quenched alloy and 3 wt.%M(M=CoS,CoS_(2),MoS_(2))catalyst were prepared by high-speed vibration ball *** effects of metal sulfides on the hydrogenation and dehydrogenation dynamics of alloys were *** results show that the as-milled composites contain a large number of amorphous embedded by a small amount of nanocrystals,and there are many point *** ball milling,the crystal grain size in the composites containing CoS is relatively larger,followed by CoS_(2)and MoS_(2)*** hydrogenation,the amorphous phase is crystallized to form Mg_(2)NiH_(4),YH_(3),Pr_(8)H_(18.96),Sm_(3)H_7,Mg,Co or Mo phases,however,Mg_(2)Ni,YH_(2),PrH_(2)and Ni_(3)Y phases appeared after *** maximum hydrogenation capacity of the composites containing CoS,CoS_(2)and MoS_(2)are 3.939,4.265 and 4.507 wt.%,*** hydrogenation saturation ratio of composite containing MoS_(2)is higher than that of the composites containing CoS and CoS_(2).The dehydrogenation activation energy of the composites containing CoS,CoS_(2)and MoS_(2)is 107.76,68.43 and 63.28 ***^(-1).H_(2).On the improvement of hydrogen storage performance of Mg_(20)Pr_(1)Sm_(3)Y_(1)Ni_(10)alloy,the catalytic effect of MoS_(2)sulfide is better than that of CoS_(2)sulfide,and which is better than CoS sulfide.

关键词： Mg_(20)Pr_(1)Sm_(3)Y_(1)Ni_(10)as-quenched alloy CoS CoS_(2)and MoS_(2)sulfide Milling Activation energy Hydrogen storage dynamics

Electrical tree degradation of MgO/epoxy resin composites at different voltage frequencies

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High Voltage 2024年第3期9卷 581-590页

作者： Yunxiao zhang wenxin Lin Yuanxiang Zhou Weiwei Xing Jiayu Cheng Chenyuan Teng College of Electrical engineering and automation Fuzhou UniversityFujian Key Laboratory of New Energy Generation and Power ConversionFuzhouChina State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical EngineeringTsinghua UniversityBeijingChina

Electrical tree degradation is one of the main causes of insulation failure in high-frequency *** tree degradation is studied on pure epoxy resin(EP)and MgO/EP composites at frequencies ranging from 50 Hz to 130 *** results show that the tree initiation voltage of EP decreases,while the growth rate and the expansion coefficient increase with ***,the bubble phenomenon at high frequencies in EP composites is *** with trap distribution character-istics within the material,the intrinsic mechanism of epoxy composites to inhibit the growth of the electrical tree at different frequencies is *** can be concluded that more deep traps and blocking effect are introduced by doping nano-MgO into EP bulks,which can improve the electrical tree resistance performance of EP composites in a wide frequency range.

关键词： composites tree Electrical

CAV driving safety monitoring and warning via V2X-based edge computing system

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Frontiers of engineering Management 2024年第1期11卷 107-127页

作者： Cheng CHANG Jiawei zhang Kunpeng zhang Yichen ZHENG Mengkai SHI Jianming HU Shen LI Li LI department of automation Tsinghua UniversityBeijing 100084China College of Electrical engineering Henan University of TechnologyZhengzhou 450001China Nebula Link Technology Co. Ltd.Beijing 100080China department of Civil engineering Tsinghua UniversityBeijing 100084China

Driving safety and accident prevention are attracting increasing global *** safety monitoring systems often face challenges such as limited spatiotemporal coverage and accuracy,leading to delays in alerting drivers about potential *** study explores the use of edge computing for monitoring vehicle motion and issuing accident warnings,such as lane departures and vehicle *** traditional systems that depend on data from single vehicles,the cooperative vehicle-infrastructure system collects data directly from connected and automated vehicles(CAVs)via vehicle-to-everything *** approach facilitates a comprehensive assessment of each vehicle’s *** propose algorithms and specific data structures for evaluating accident risks associated with different ***,we examine the prerequisites for data accuracy and transmission delay to enhance the safety of CAV *** efficacy of this framework is validated through both simulated and real-world road tests,proving its utility in diverse driving conditions.

关键词： driving safety accident prevention connected and automated vehicles edge computing

A Data-Driven Real-Time Trajectory Planning and Control Methodology for UGVs Using LSTMRDNN

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IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1292-1294页

作者： Kaiyuan Chen Runqi Chai Runda zhang zhida Xing Yuanqing Xia Guoping Liu Vanke School of Public Health Institute for Healthy ChinaTsinghua UniversityBeijing 100084 School of automation Beijing Institute of TechnologyBeijing 100081 department of Electronic and Electrical engineering Southern University of Science and TechnologyShenzhen 518055China

Dear Editor,This letter presents a novel data-driven trajectory planning and control scheme for the unmanned ground vehicles(UGVs).A recent work[1]has demonstrated the effectiveness of approximating the optimal state ... 详细信息

关键词： LSTM UGV neural

Recent Progress of Full‑Field Three‑Dimensional Shape Measurement Based on Phase Information

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Nanomanufacturing and Metrology 2024年第2期7卷 26-41页

作者： Yajing Bai Zonghua zhang Shuai Fu Hongwei Zhao Yubo Ni Nan Gao Zhaozong Meng Zeqing Yang Guofeng zhang Wei Yin School of Mechanical engineering Hebei University of TechnologyTianjin 300401China School of Mechanical engineering Xi’an Jiaotong UniversityXi’an 710049ShaanxiChina National Key Laboratory of Strength and Structural Integrity Aircraft Strength Research Institute of ChinaXi’an 710065ShaanxiChina

Full-field three-dimensional(3D)measurement technology based on phase information has become an indispensable part of geometric dimension measurement in modern scientific research and engineering *** field has been developing and evolving for the study of highly reflective phenomena,diffuse reflections,and specular surfaces,and many novel methods have emerged to increase the speed of measurements,enhance data accuracy,and broaden the robustness of the ***,we will discuss the latest research progress in full-field 3D shape measurement based on phase information systematically and ***,the fundamentals of 3D shape measurement based on phase information are introduced,namely,phase-shifting and transform-based ***,recent technological innovations are highlighted,including increases in measurement speed and automation and improvements in robustness in complex *** particular,the challenges faced by these technological advances in solving highly dynamic,composite surface measurement problems are presented,i.e.,with multiexposure techniques proposed for high dynamics that extend the dynamic range of the camera to reduce the effects of overexposure but increase the cost of time and have high hardware requirements,fringe adaptive techniques that overcome light variations but are computationally complex,and multipolarized camera techniques that reduce the effects of light variations but are sensitive to the light ***,the phase-shifting method combined with coding is proposed to improve the measurement speed,but the accuracy is slightly *** learning techniques are proposed to cope with measurements in complex environments,but the dataset computation process is ***,future research directions are suggested,and the challenges are ***,this work provides a reference for researchers and engineers.

关键词： 3D measurement Phase information Fringe projection Phase measuring deflectometry