相关参考文献
注意：仅列出部分参考文献，下载原文获取全部文献信息。
Article
Automation & Control Systems
Peyman Ahmadi et al.
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
(2023)
Article
Automation & Control Systems
Qiuyan Cui et al.
Summary: This paper investigates the optimisation problem of second-order multi-agent systems and proposes distributed optimisation algorithms based on sampling data. Two types of sampling techniques, aperiodic and dynamic event-triggered, are utilized. The algorithms also employ the proportional integral (PI) strategy. It is proven that the proposed algorithms solve the optimisation problem under the assumption of a strongly convex global cost function. The effectiveness of the algorithms is demonstrated through numerical simulations.
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
(2023)
Article
Automation & Control Systems
Zhicheng Kou et al.
Summary: This paper proposes a test-based model-free adaptive iterative learning control algorithm (TB-MFAILC) with strong robustness. The algorithm improves the convergence issue of existing model-free adaptive iterative learning control algorithms in noisy environments. The convergence and robustness of the proposed algorithm are demonstrated in different environments, and its effectiveness is illustrated through numerical comparison simulations.
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
(2023)
Article
Computer Science, Interdisciplinary Applications
Wei Li et al.
Summary: The paper introduces a new framework MRDO-UPM to address parameter and metamodeling uncertainties in multidisciplinary design optimization. The effectiveness of the new framework is validated through numerical examples and practical design.
ENGINEERING WITH COMPUTERS
(2022)
Article
Computer Science, Interdisciplinary Applications
Jian Song et al.
Summary: This work presents a cascade optimization method combining topology optimization with shape optimization to design a high-performance twin-web turbine disk. The optimized twin-web turbine disk fulfills the design requirements of an aero-engine turbine disk, with a weight reduction of 21.35% and an improvement of 8.5% in strain energy compared to the reference single-web turbine disk.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2022)
Article
Computer Science, Artificial Intelligence
Zhengping Liang et al.
Summary: This article proposes an evolutionary many-task optimization algorithm, EMaTO-MKT, based on a multisource knowledge transfer mechanism. The algorithm adaptively determines the probability of using knowledge transfer and balances the self-evolution and knowledge transfer among tasks. It selects multiple highly similar tasks as learning sources and applies a knowledge transfer strategy based on local distribution estimation. Experimental results show the competitiveness of EMaTO-MKT in solving many-task optimization problems.
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
(2022)
Article
Chemistry, Multidisciplinary
Cheng Yan et al.
Summary: An effective integrated design optimization method is developed to reduce maximum von Mises stress around vent holes through various hole shapes, strength analysis, and a delayed particle swarm optimization algorithm. Results show that the SDPSO algorithm outperforms other PSO algorithms in optimization capability, numerical robustness, and convergence speed, with the four-arc hole being the most effective in reducing stress.
APPLIED SCIENCES-BASEL
(2022)
Article
Automation & Control Systems
Guangyan Bao et al.
Summary: This paper surveys the cooperative control of heterogeneous multi-agent systems (HMASs) subject to specific constraints. HMASs are classified into weak and strong categories based on different cooperative behaviors, and control strategies are discussed for dealing with various constraints on agent dynamics and communication networks. The latest results on cooperative control under different constraints are summarized, and conclusions are drawn along with possible future research directions.
SYSTEMS SCIENCE & CONTROL ENGINEERING
(2022)
Article
Automation & Control Systems
Han Li et al.
Summary: This paper reviews the use of mathematical tools to enhance LFIA performance, and proposes a novel taxonomy. It also presents the outlook of developing POCT in conjunction with other state-of-the-art techniques, and highlights the importance of applying computational intelligence methods in boosting POCT development.
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
(2022)
Article
Computer Science, Artificial Intelligence
Han Li et al.
Summary: In this paper, a novel ranking-system-based switching particle swarm optimizer (RSPSO) is proposed. The algorithm enhances communication among swarm and improves optimization performance through strategies like switching stages and dynamic neighborhood. Experimental results demonstrate that the proposed algorithm performs excellently on various benchmark tests.
Article
Automation & Control Systems
Zhengping Liang et al.
Summary: The EMT-PD algorithm improves convergence performance by adjusting search step size and dynamically changing search range based on population distribution. This two-stage adaptive knowledge transfer approach reduces negative transfer effects and enhances population diversity, helping to escape local optima. Experimental results demonstrate the superiority of EMT-PD in multitasking multiobjective optimization.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2022)
Article
Automation & Control Systems
Zuwei Huang et al.
Summary: In this study, a non-uniform mutation sparrow search algorithm (NMSSA) is proposed to improve the issues of local optima and zero locations preference in the traditional sparrow search algorithm (SSA). By introducing different strategies, including the tent chaos map, generalized opposition-based learning, adaptive weight, and non-uniform mutation, experimental results show that NMSSA performs well in benchmark functions, engineering optimization, and image segmentation.
SYSTEMS SCIENCE & CONTROL ENGINEERING
(2022)
Article
Automation & Control Systems
Yuanye Wei et al.
Summary: This paper proposes a simplified slime mould algorithm (SSMA) to solve the coverage problem in wireless sensor networks (WSN). Through experiments and comparisons with other meta-heuristic algorithms, the SSMA demonstrates competitive, outstanding performance, and effectiveness. It can effectively control the energy of network nodes, improve the quality of service, and extend the network survival time.
SYSTEMS SCIENCE & CONTROL ENGINEERING
(2022)
Review
Engineering, Multidisciplinary
Debiao Meng et al.
Summary: This study provides a comprehensive review of the theory of reliability-based multidisciplinary design optimization (RBDMO), including the reliability analysis methods for different uncertainties and the decoupling strategies for RBDMO. It introduces three commonly used RBDMO methods and their mathematical models through specific cases. Future challenges in RBDMO are also discussed.
INTERNATIONAL JOURNAL OF STRUCTURAL INTEGRITY
(2022)
Article
Computer Science, Artificial Intelligence
Xiangyu Wang et al.
Summary: This article proposes an enhanced competitive swarm optimization algorithm assisted by a strongly convex sparse operator to address sparse multiobjective optimization problems, achieving superior performance compared to state-of-the-art methods in both test problems and application examples.
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
(2022)
Article
Automation & Control Systems
Nianyin Zeng et al.
Summary: In this article, a dynamic-neighborhood-based switching PSO (DNSPSO) algorithm is proposed with improved velocity update mechanism and learning strategy. The differential evolution algorithm is successfully hybridized with the particle swarm optimization algorithm to enhance the solution accuracy for multimodal optimization problems.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Automation & Control Systems
Jun Hu et al.
Summary: This paper reviews the latest state estimation schemes for complex dynamical networks (CDNs), covering various methods under different performance indices and focusing on protocol-based and compensation-based state estimation approaches. Challenging problems for future research are outlined to promote theoretical developments in related fields.
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
(2021)
Article
Automation & Control Systems
Yuan Liu et al.
Summary: The Pareto-based approach is not well suited for optimization problems with a large number of objectives, prompting the proposal of a new algorithm in this article to address this issue. The algorithm tackles the problem by eliminating DRSs using an interquartile range method and balancing convergence and diversity through a penalty mechanism of alternating operations. Experimental results show that the proposed algorithm generally outperforms its competitors on a variety of test functions with 3-15 objectives.
IEEE TRANSACTIONS ON CYBERNETICS
(2021)
Article
Computer Science, Artificial Intelligence
Nianyin Zeng et al.
Summary: The paper proposes a competitive mechanism integrated whale optimization algorithm (CMWOA) for multi-objective optimization problems. By introducing a novel competitive mechanism and improving the calculation of crowding distance, the convergence and accuracy of the algorithm are enhanced. Additionally, concatenating differential evolution (DE) into the population with different adjusting strategies for key parameters further improves the overall performance.
Article
Engineering, Aerospace
Jiandong Guo et al.
Summary: This paper presents an innovative and efficient 3D autonomous obstacle algorithm for UAVs, utilizing circular arc trajectories to avoid obstacles and transforming irregular obstacles into standard convex bodies for trajectory generation. By defining rules for obstacle detection, avoidance direction, and success criteria, the algorithm is able to effectively avoid both static and dynamic obstacles in simulation scenarios.
INTERNATIONAL JOURNAL OF AEROSPACE ENGINEERING
(2021)
Article
Automation & Control Systems
Baoye Song et al.
Summary: This paper introduces a new workspace model to describe the environment of coal mines and develops an improved ant colony optimization algorithm for path planning of coal mine robots. Simulation experiments confirm the effectiveness and superiority of the new approach.
SYSTEMS SCIENCE & CONTROL ENGINEERING
(2021)
Article
Automation & Control Systems
Lin Xu et al.
Summary: This paper proposes an improved particle swarm optimization algorithm, PSO-AWDV, which adaptively updates velocity inertia weight based on the evolutionary state of the particle swarm evaluated via a new estimation method. Experimental results confirm that the performance of PSO-AWDV is superior to several well-known PSO variants and intelligent optimization algorithms.
SYSTEMS SCIENCE & CONTROL ENGINEERING
(2021)
Article
Engineering, Aerospace
Cheng Yan et al.
AEROSPACE SCIENCE AND TECHNOLOGY
(2020)
Article
Thermodynamics
Lei Li et al.
INTERNATIONAL JOURNAL OF THERMAL SCIENCES
(2020)
Article
Computer Science, Artificial Intelligence
Shouyong Jiang et al.
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
(2018)
Article
Engineering, Industrial
Dongliang Cui et al.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2017)
Editorial Material
Computer Science, Artificial Intelligence
Ye Tian et al.
IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE
(2017)
Article
Thermodynamics
Guo Li et al.
INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER
(2017)
Article
Engineering, Aerospace
Dian-Yin Hu et al.
JOURNAL OF AEROSPACE ENGINEERING
(2017)
Article
Automation & Control Systems
Hui Li et al.
IEEE TRANSACTIONS ON CYBERNETICS
(2017)
Article
Computer Science, Interdisciplinary Applications
Seyedali Mirjalili et al.
ADVANCES IN ENGINEERING SOFTWARE
(2016)
Article
Computer Science, Artificial Intelligence
Rui Wang et al.
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
(2016)
Article
Engineering, Mechanical
Andrea Rindi et al.
JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER-TRANSACTIONS OF THE ASME
(2016)
Article
Computer Science, Artificial Intelligence
Qingfu Zhang et al.
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
(2007)
Review
Computer Science, Artificial Intelligence
Simon Huband et al.
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
(2006)
Article
Computer Science, Artificial Intelligence
Eckart Zitzler et al.
EVOLUTIONARY COMPUTATION
(2000)
