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Frontiers of Structural and Civil Engineering 2022年第10期16卷 1267-1286页

作者： Thuy-Anh NGUYEN Hai-Bang LY Van Quan TRAN Department of Civil Engineering University of Transport TechnologyHanoi 100000Vietnam

Shear failure of slender reinforced concrete beams without stirrups has surely been a complicated occurrence that has proven challenging to adequately *** primary purpose of this work is to develop machine learning models capable of reliably predicting the shear strength of non-shear-reinforced slender beams(SB).A database encompassing 1118 experimental findings from the relevant literature was compiled,containing eight distinct *** Boosting(GB)technique was developed and evaluated in combination with three different optimization algorithms,namely Particle Swarm optimization(PSO),Random Annealing optimization(RA),and Simulated Annealing optimization(SA).The findings suggested that GB-SA could deliver strong prediction results and effectively generalizes the connection between the input and output *** values and two-dimensional PDP analysis were then carried *** may use the findings in this work to define beam’s geometrical components and material used to achieve the desired shear strength of SB without reinforcement.

关键词： slender beam shear strength gradient boosting optimization algorithms

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EXPERIMENTS TO TRACK STORMS USING MODERN optimization algorithms

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Journal of Tropical Meteorology 2010年第3期16卷 280-291页

作者：李南魏鸣 Key Laboratory of Meteorological Disaster of Ministry of Education Nanjing University of Information Science & Technology School of Atmospheric Physics Nanjing University of Information Science & Technology State Key Laboratory of Severe Weather Chinese Academy of Meteorological Sciences

Storm identification and tracking based on weather radar data are essential to nowcasting and severe weather warning. A new two-dimensional storm identification method simultaneously seeking in two directions is proposed, and identification results are used to discuss storm tracking algorithms. Three modern optimization algorithms （simulated annealing algorithm, genetic algorithm and ant colony algorithm） are tested to match storms in successive time intervals. Preliminary results indicate that the simulated annealing algorithm and ant colony algorithm are effective and have intuitionally adjustable parameters, whereas the genetic algorithm is unsatisfaetorily constrained by the mode of genetic operations Experiments provide not only the feasibility and characteristics of storm tracking with modern optimization algorithms, but also references for studies and applications in relevant fields.

关键词： raw weather radar data storm identification and tracking optimization algorithms

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optimization algorithms for Flexible Protein-Protein Docking

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Optimization Algorithms for Flexible Protein-Protein Docking

On Comparing Six optimization algorithms for Network-based Wind Speed Forecasting

第三届数字制造与自动化国际会议

作者： Zhao Li Zhang Tianchi Zhang Jing College of Computer Science and Technology Harbin Engineering University Department of computer science and Information Engineering Harbin Normal University

The flexibility in protein docking is a major challenge in bioinformatic research.. Protein docking problem is essentially an optimization problem. In this review we describe the methods of existing flexible protein-protein docking ,focusing on the optimization algorithms . We divide the different methods into categories for presenting clearly.

关键词： flexible docking optimization algorithms protein-protein docking

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On Comparing Six Optimization Algorithms for Network-based W...

Development of Fixture Layout optimization for Thin-Walled Parts:A Review

第37届中国控制会议

作者： Huanjie Tao Xiaobo Lu School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSoutheast University

Network-based wind speed forecasting has played an important role in the power system. The network parameters optimization is an important issue, and different optimization algorithms are believed to result in different forecasting accuracies. In this paper, six network parameters optimization algorithms, including Gradient descent, Momentum, Ada Grad, RMSprop, Adam, and Adadelta, are implemented and compared in the application of wind speed forecasting. As a case study, this paper uses a wind speed data obtained from Ningxia, China. The performance is evaluated by three metrics, namely, mean absolute error（MAE）, root mean square error（RMSE）, and mean absolute percentage error（MAPE）. The experiment results show that, Adam algorithm and RMSprop algorithm achieve better forecasting accuracy and less training time than the other optimization algorithms. This study can be a guide to the selection of optimization algorithms on wind speed forecasting problems for researchers.

关键词： Wind speed forecasting Back-propagation neural network Forecasting accuracy optimization algorithms

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Chinese Journal of Mechanical Engineering 2024年第1期37卷 15-39页

作者： Changhui Liu Jing Wang Binghai Zhou Jianbo Yu Ying Zheng Jianfeng Liu School of Mechanical Engineering Tongji UniversityShanghai 201804China Shanghai Jiaotong University Shanghai 200240China Shanghai Waigaoqiao Shipbuilding Co. Ltd.Shanghai 200137China

An increasing number of researchers have researched fixture layout optimization for thin-walled part assembly during the past ***,few papers systematically review these *** analyzing existing literature,this paper summarizes the process of fixture layout optimization and the methods *** process of optimization is made up of optimization objective setting,assembly variation/deformation modeling,and fixture layout *** paper makes a review of the fixture layout for thin-walled parts according to these three ***,two different kinds of optimization objectives are *** usually consider in-plane variations or out-of-plane deformations when designing ***,modeling methods for assembly variation and deformation are divided into two categories:Mechanism-based and data-based *** common methods are discussed *** that,optimization algorithms are reviewed *** are two kinds of optimization algorithms:Traditional nonlinear programming and heuristic ***,discussions on the current situation are *** research direction of fixture layout optimization in the future is discussed from three aspects:Objective setting,improving modeling accuracy and optimization ***,a new research point for fixture layout optimization is *** paper systematically reviews the research on fixture layout optimization for thin-walled parts,and provides a reference for future research in this field.

关键词： Thin-walled parts Assembly quality Fixture layout optimization Modeling methods optimization algorithms

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Advanced Machine Learning Methods for Prediction of Blast-Induced Flyrock Using Hybrid SVR Methods

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Computer Modeling in Engineering & Sciences 2024年第8期140卷 1595-1617页

作者： Ji Zhou Yijun Lu Qiong Tian Haichuan Liu Mahdi Hasanipanah Jiandong Huang College of Civil and Environmental Engineering Hunan University of Science and EngineeringYongzhou425006China Hunan Provincial Key Laboratory of Intelligent Protection and Utilization Technology in Masonry Artifacts Hunan University of Science and EngineeringYongzhou425006China School of Civil Engineering Guangzhou UniversityGuangzhou510006China Institute of Research and Development Duy Tan UniversityDa Nang550000Vietnam School of Engineering&Technology Duy Tan UniversityDa Nang550000Vietnam

Blasting in surface mines aims to fragment rock masses to a proper ***,flyrock is an undesirable effect of blasting that can result in human *** this study,support vector regression(SVR)is combined with four algorithms:gravitational search algorithm(GSA),biogeography-based optimization(BBO),ant colony optimization(ACO),and whale optimization algorithm(WOA)for predicting flyrock in two surface mines in ***,three other methods,including artificial neural network(ANN),kernel extreme learning machine(KELM),and general regression neural network(GRNN),are employed,and their performances are compared to those of four hybrid SVR *** modeling,the measured and predicted flyrock values are validated with some performance indices,such as root mean squared error(RMSE).The results revealed that the SVR-WOA model has the most optimal accuracy,with an RMSE of 7.218,while the RMSEs of the KELM,GRNN,SVR-GSA,ANN,SVR-BBO,and SVR-ACO models are 10.668,10.867,15.305,15.661,16.239,and 18.228,***,combining WOA and SVR can be a valuable tool for accurately predicting flyrock distance in surface mines.

关键词： Flyrock induced by blasting optimization algorithms SVR GRNN

Multi-objective wolf pack algorithm based on adaptive grouping strategy and crowding distance

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Kongzhi yu Juece/Control and Decision 2024年第11期39卷 3772-3780页

作者： Zhao, Jia Lv, Feng Xiao, Ren-Bin Fan, Tang-Huai Dong, Wen-Fei Wang, Hui School of Information Engineering Nanchang Institute of Technology Nanchang 330000 China Nanchang Key Laboratory of IoT Perception and Collaborative Computing for Smart City Nanchang Institute of Technology Nanchang 330099 China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan 430074 China

In view of the wolf pack algorithm has good solving ability in single objective optimization problems, a multi-objective wolf pack algorithm (MOWPA-AG) based on adaptive grouping and updating of crowded distance is proposed by taking the advantages of the wolf pack biological habit and being used to solve multi-objective optimization problems. Firstly, an adaptive grouping strategy considering population diversity and dispersed search is proposed to simulate family aggregation in wolf packs. The strategy stratifies populations, separates populations and helps population diffusion search Pareto optimal solutions. Then, a population renewal mechanism based on crowding distance is designed, which enables the population to maintain rapid evolution while obtaining the optimal solution set. In order to verify the performance of the proposed algorithm, nine different benchmark testing problems are tested, and the effectiveness of the proposed algorithm is verified by comparing with other classic and recent multi-objective optimization algorithms. Finally, the MOWPA-AG is applied to solve the problem of four-bar truss structure in practical engineering, which shows the universality of the proposed algorithm. © 2024 Northeast University. All rights reserved.

关键词： optimization algorithms

optimization-inspired manual architecture design and neural architecture search

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Science China(Information Sciences) 2023年第11期66卷 100-112页

作者： Yibo YANG Zhengyang SHEN Huan LI Zhouchen LIN JD Explore Academy School of Mathematical Sciences Peking University Institute of Robotics and Automatic Information Systems College of Artificial Intelligence Nankai University Key Lab of General Artificial Intelligence School of Intelligence Science and Technology Peking University Institute for Artificial Intelligence Peking University Pazhou Lab

Neural architecture has been a research focus in recent years due to its importance in deciding the performance of deep networks. Representative ones include a residual network(Res Net) with skip connections and a dense network(Dense Net) with dense connections. However, a theoretical guidance for manual architecture design and neural architecture search(NAS) is still lacking. In this paper, we propose a manual architecture design framework, which is inspired by optimization algorithms. It is based on the conjecture that an optimization algorithm with a good convergence rate may imply a neural architecture with good performance. Concretely, we prove under certain conditions that forward propagation in a deep neural network is equivalent to the iterative optimization procedure of the gradient descent algorithm minimizing a cost function. Inspired by this correspondence, we derive neural architectures from fast optimization algorithms,including the heavy ball algorithm and Nesterov’s accelerated gradient descent algorithm. Surprisingly, we find that we can deem the Res Net and Dense Net as special cases of the optimization-inspired *** architectures offer not only theoretical guidance, but also good performances in image recognition on multiple datasets, including CIFAR-10, CIFAR-100, and Image Net. Moreover, we show that our method is also useful for NAS by offering a good initial search point or guiding the search space.

关键词： deep neural network manual architecture design neural architecture search image recognition optimization algorithms learning-based optimization

Achieving geometric convergence for distributed optimization with Barzilai-Borwein step sizes

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Science China(Information Sciences) 2022年第4期65卷 280-281页

作者： Juan GAO Xin-Wei LIU Yu-Hong DAI Yakui HUANG Peng YANG School of Artificial Intelligence Hebei University of Technology Institute of Mathematics Hebei University of Technology LSEC Academy of Mathematics and Systems Science Chinese Academy of Sciences School of Mathematical Sciences University of Chinese Academy of Sciences

Dear editor,We consider distributed optimization, which can be formulated to minimize the average of all local objective functions:■where each local function f;:■ is L;-smooth and μ;-strongly convex and known only ... 详细信息

关键词： distributed optimization multi-agent network Barzilai-Borwein step sizes optimization algorithms convergence rate

Quantum algorithms of state estimators in classical control systems

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Science China(Information Sciences) 2020年第9期63卷 243-254页

作者： Kai LI Hongyi DAI Ming ZHANG College of Intelligence Science National University of Defense Technology College of Liberal Arts and Sciences National University of Defense Technology

In this paper, quantum algorithms are applied to the design of state estimators in classical control systems under the condition that quantum algorithms can be physically implemented. We demonstrate that the design of state estimators can be solved by quantum algorithms, which may achieve significant acceleration in comparison to traditional classical algorithms. The time complexity can be reduced from O(n6) to O(qn)when the system matrix is sparse and the condition number κ and the reciprocal of precision ? are small in size O(poly log(n)), where n is the dimension of state x(t) and q is the dimension of input u(t). Our research will provide an entire quantum scheme of constructing state estimators and can be regarded as an attempt to widen application scope of quantum computation.

关键词： quantum computation estimators for linear systems optimization algorithms quantum acceleration time complexity