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International Conference on Mechatronics Engineering and Computing Technology (ICMECT)

作者： Li, Yaolei Wang, Congxian Li, Zhenjia Hebei Inst Phys Educ Fac Sports Training Shijiazhuang 050041 Peoples R China Heibei jiaotong Vocat & Tech Coll Dept Basic Courses Sports Teaching & Res Sect Shijiazhuang 050091 Peoples R China

ISBN: (纸本)9783038351153

The technology teaching of university basketball general course is a focus which all sectors of the community should pay more attention. How will the technology teaching of university basketball general course carry out optimization of integration, to play the biggest role, is also the key point of this paper. This paper from the main content of post-modern education and university basketball general course technology teaching, to understand the current situation of university basketball education, and construct basketball general course technology evaluation system. At the same time, using fuzzy evaluation method to do statistical analysis on the situation of basketball general course technology education, and in a targeted manner to set up teaching mode of basketball general course technology under Post-modern educational perspective, use the society, network, universities' and other resources effectively, to sharing the resources, realize technology education and the optimization configuration of resource.

关键词： Fuzzy evaluation Technical model optimization algorithm Weighting factor Project matrix

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optimization methods rooted in optimal control

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Science China(Information Sciences) 2024年第12期67卷 272-280页

作者： Huanshui ZHANG Hongxia WANG Yeming XU Ziyuan GUO School of Electrical and Automation Engineering Shandong University of Science and Technology School of Control Science and Engineering Shandong University

In the paper, we investigate the optimization problem(OP) by applying the optimal control method. The optimization problem is reformulated as an optimal control problem(OCP) where the controller(iteration updating) is designed to minimize the sum of costs in the future time instant, which thus theoretically generates the “optimal algorithm”(fastest and most stable). By adopting the maximum principle and linearization with Taylor expansion, new algorithms are proposed. It is shown that the proposed algorithms have a superlinear convergence rate and thus converge more rapidly than the gradient descent;meanwhile, they are superior to Newton's method because they are not divergent in general and can be applied in the case of a singular or indefinite Hessian matrix. More importantly, the OCP method contains the gradient descent and the Newton's method as special cases, which discovers the theoretical basis of gradient descent and Newton's method and reveals how far these algorithms are from the optimal algorithm. The merits of the proposed optimization algorithm are illustrated by numerical experiments.

关键词： optimal control optimization methods optimization algorithm maximum principle superlinear convergence

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Tolerance-cost optimization for multi-cabin spacecraft assembly considering form errors

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE 2025年

作者： Yang, Jiangxin Wu, Chengjin Shao, Nan Cao, Yanlong Anwer, Nabil Cao, Yanpeng Zhejiang Univ Sch Mech Engn Key Lab Adv Mfg Technol Zhejiang Prov Hangzhou Peoples R China Beijing Inst Technol Sch Mech Engn Beijing Peoples R China Univ Paris Saclay ENS Paris Saclay LURPA 4 Ave Sci Gif Sur Yvette France

Tolerance-cost optimization plays an important role in trade-off between deviation reduction and manufacturing cost. However, very few studies focus on the assembly accuracy of the cabin using a more efficient tolerance allocation considering both quality and cost issues. Therefore, this paper proposes a tolerance-cost optimization method for multi-cabin assembly of spacecrafts based on the cloud model based genetic algorithm (CGA). To improve the accuracy of tolerance analysis, a comprehensive assembly accuracy analysis method is used, composed of tolerance representation and propagation. For tolerance representation, skin model shape and small displacement torsor theory are used to respectively represent the form and position errors. For tolerance propagation, the integrated Jacobian-skin model shapes model is used to compute the accumulative results of deviation. Simulation results demonstrate the capability of the proposed method to predict the assembly accuracy of cabins with non-ideal surfaces. To improve the efficiency of the optimization, CGA is utilized as an optimization technique. Compared with traditional optimization methods, simulation analysis shows superior performance of parameter optimization in the problem of tolerance-cost optimization of multi-cabin spacecraft.

关键词： Assembly tolerance analysis tolerance allocation spacecraft cabin optimization algorithm skin model shape

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optimization algorithm of Manipulator Robot Performances 4

Optimization Algorithm of Manipulator Robot Performances

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4th IEEE Annual International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER)

作者： Belaidi, Abderrahmane Belaidi, Hadjira Univ Mhamed Bougara Boumerdes Fac Chem & Hydrocarbons Boumerdes 35000 Algeria UMBB Univ IGEE Signals & Syst Lab Boumerdes 35000 Algeria Adv Technol Dev Ctr CDTA Algiers 16303 Algeria

ISBN: (纸本)9781479936694

One aim of controlling a manipulator robot is to maximize its performances such as accuracy, speed, time etc.. However, limiting the power of actuators causes a limitation of their generalized accelerations and velocities;this is due to the high inertial forces, which create dangerous voltages at the machines elements. This paper propose an algorithm to solve the problem of maximizing the manipulator performances considering that the end-effector position and orientation is characterized by a 6x1 vector i.e., six degrees of freedom;moreover, the need to move the end-effector from the start position to the target with a minimum time, without violating its boundaries. The presented solution is well suited to this context. It is optimal with respect to time constraints, and it allows a direct calculation.

关键词： manipulator robot optimization algorithm speed acceleration minimal time

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Design and optimization of Multilayered Microwave Absorber Structures for X-Band Frequencies: Application on Composite Materials Comprising Ceramic, Polyaniline/Magnetite, and Carbon Nanotubes

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INTERNATIONAL JOURNAL OF NUMERICAL MODELLING-ELECTRONIC NETWORKS DEVICES AND FIELDS 2025年第1期38卷

作者： Karim, Benzaoui Achour, Ales Amin, Medjaouri Youcef Abdelhalim, Zaoui Ecole Mil Polytech Electromagnet Compatibil EMC Lab Algiers Algeria Ecole Natl Super Technol Algiers Algeria

The characteristics of multilayered microwave absorbing materials are very efficient compared with those of single layer. In this article, a hybrid optimization algorithm (genetic algorithm + pattern search) combined with transmission line matrix method has been presented. The selection of parameters, including the arrangement of layers, thickness of layers, absorption index, and shielding efficiency, forms the foundation of this process. The optimization algorithm was applied to two new multilayered structures. The first structure consists of conductive layers (CLs) of carbon nanotube (CNT) with ceramic layers of zirconium dioxide ZrO2. The second structure includes CLs of CNT with layers based on magnetite polyaniline nanomaterial (PANI_Fe3O4). Performances of both structures were evaluated in the X-band frequency range. Simulation results showed that both designs have higher absorption index picks (> 90%) and, low S-11 magnitude value with low layer thickness. This approach offers a solid foundation for future experimental trials in the development of efficient microwave absorbing and shielding structures with tunable electromagnetic performances suitable for X-band applications.

关键词： ceramic layer multilayer microwave absorbing optimization algorithm polyaniline/magnetite shielding effectiveness

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Energy integration of LNG cold energy power generation and liquefied air energy storage: Process design, optimization and analysis

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ENERGY 2025年 321卷

作者： Li, Ran Tang, Feiran Pan, Jie Cao, Qinghan Hu, Tinglong Wang, Ke Xian Shiyou Univ Coll Petr Engn Xian 710065 Peoples R China Xian Shiyou Univ Univ Shaanxi Prov Engn Res Ctr Safety & Energy Saving Oil & Gas Stor Xian 710065 Peoples R China China Univ Petr Coll Mech & Transportat Engn Beijing 102249 Peoples R China

Liquefied natural gas (LNG) has a large amount of cold energy, and recovering LNG cold energy can not only reduce dependence on traditional energy and promote sustainable energy development but also reduce pollutant emissions, and liquified air energy storage (LAES) is an advanced energy storage technology, but its electrical round trip efficiency (ERTE) is low due to the lack of sufficient cold energy. Thus, to improve the efficiency and benefit of LNG cold energy utilization and the ERTE of LAES, an integrated power generation system combining organic Rankine cycle (ORC) with LAES driven by LNG cold energy (denoted as LNG-ORC-LAES) is proposed in this paper. The system operates in two modes, utilizing LNG cold energy at peak and off-peak times. The system is optimized under different peak electricity price scenarios by using multi-objective optimizations to achieve better performance. The LINMAP (Linear Programming Technique for Multidimensional Analysis of Preference) and TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) methods can dimensionless the optimization results and calculate the distance between each point on the optimal Pareto surfaces and the ideal point, so the two decision methods are used to screen the optimization results. The exergy efficiency and specific net output power of existing similar systems are similar to 70.31 % and similar to 94.75 kJ/kgLNG, but they can achieve 72.26 % and 124.43 kJ/kgLNG respectively after multi-objective optimization in the proposed system, and the high net present value (NPV) is obtained, the optimized system exhibits superior performance than other similar systems. The energy and exergy analysis demonstrate that the LNG cold energy utilization ratio can reach 81.96 % under optimal working conditions, the LNG cold exergy can be fully utilized by LAES. The results show that the proposed system has industrial and economic feasibility, which provides a design concept with practical significan

关键词： LNG cold energy Organic rankine cycle Liquefied air energy storage Economic analysis optimization algorithm

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Application of Ant Colony optimization Improved Clustering algorithm in Malicious Software Identification

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INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2024年第1期15卷 1031-1039页

作者： Qian, Yong Sichuan Coll Architectural Technol Int Sch Tech Educ Deyang 618000 Peoples R China

Due to the increasing threat of malware to computer systems and networks, traditional malware detection and recognition technologies face difficulties and limitations. Therefore, exploring new methods to improve the accuracy and efficiency of malware identification has become an urgent need. This study introduces ant colony algorithm to optimize traditional clustering algorithms and algorithm parameters. The experimental results showed that the improvement rates of the improved algorithm in accuracy, echo value, and false alarm rate were 0.253, 0.115, and 0.056, respectively. The accuracy on the training and validation sets continued to increase and the loss curve continued to decrease. In addition, the improved algorithm had stronger modeling ability for data feature relationships and temporal information. This is of great help in improving the recognition ability of virus and worm software. The improved algorithm had a lower occupancy rate of computing resources compared to other algorithms, but it could also effectively monitor device operation. Compared with traditional methods, this method can more accurately identify malicious software and effectively identify malicious software samples from large-scale datasets. This is of great significance for protecting computer systems and network security.

关键词： Ant colony algorithm clustering algorithm malicious software identification computer security optimization algorithm

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Time-delayed vibration control and parameter optimization of semi-active vehicle suspension designed for random road excitation

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JOURNAL OF LOW FREQUENCY NOISE VIBRATION AND ACTIVE CONTROL 2025年

作者： Guo, Yong Li, Yong-Jing Wei, Yan-Bo Shandong Business Inst 15 Haixing Rd Yantai 264670 Shandong Peoples R China

Under the influence of road excitations, the acquisition of optimal time-delayed feedback control parameters is deemed crucial for the improvement of the vibration reduction effect of semi-active vehicle suspension systems. Moreover, different effects on vibration reduction are generally exhibited by vehicle suspension systems based on different time-delayed state feedback control. Therefore, the mechanical model of time-delayed feedback control in semi-active vehicle suspension systems is chosen as the research focus in this paper. Firstly, the optimal values of time-delayed feedback control parameters are derived through an optimization algorithm based on "equivalent harmonic excitation." Secondly, driven by the optimal values derived from optimization, this study is primarily focused on the investigation of the vibration reduction effect of time delay in a vehicle's semi-active suspension system under road excitation, thereby revealing the optimal time-delayed feedback control strategy. Finally, the study suggests that a stable state with full time delay within the effective vibration frequency range is more likely to be achieved by the semi-active vehicle suspension system based on time-delayed state feedback control of wheel vertical displacement. Additionally, the optimization efficiencies for vertical seat acceleration, vertical body acceleration, suspension travel, and tire displacement are reported as 97.73%, 98.95%, 47.30%, and 46.38%, respectively.

关键词： time-delayed feedback control vibration reduction optimization algorithm equivalent harmonic excitation optimal values

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A Hybrid K-Means plus plus and Particle Swarm optimization Approach for Enhanced Document Clustering

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IEEE ACCESS 2025年 13卷 48818-48840页

作者： Hassan, Eisha Malik, Fazila Khan, Qazi Waqas Ahmad, Nadeem Sardaraz, Muhammad Karim, Faten Khalid Elmannai, Hela Iqra Univ Islamabad Dept Comp & Technol Islamabad 44000 Pakistan Jeju Natl Univ Dept Comp Engn Jeju Si 63243 South Korea COMSATS Univ Islamabad Dept Comp Sci Attock Campus Attock 43600 Pakistan Princess Nourah bint Abdulrahman Univ Coll Comp & Informat Sci Dept Comp Sci POB 84428 Riyadh 11671 Saudi Arabia Princess Nourah bint Abdulrahman Univ Coll Comp & Informat Sci Dept Informat Technol POB 84428 Riyadh 11671 Saudi Arabia

Document Clustering has attracted the interest of many researchers who have created several solutions to this problem by combining different techniques, models, and algorithms. While famous for its simplicity, the most commonly used algorithm, K-Means, suffers from issues such as finding the optimal value for k and random initialization of the centroids. In this paper, we propose a hybrid methodology combining K-Means++ with the metaheuristic algorithm PSO to overcome the challenges of both these algorithms. K-Means++ is a smart initialization technique that selects clusters based on probability function so that they are further away from each other. Two methods, Elbow Analysis, and Silhouette Score, have been used to find the optimal value of k. The research also attempts to assess the results of the best-performing feature extraction techniques and create a combined approach using their average. Although the combined approach did not outperform the existing methods, it paved the way for further advancement and exploration of merging feature extraction techniques. The experiments were performed on four datasets: 20 Newsgroups, Reuters, WebKB, and Wine, and the results were evaluated using three evaluation metrics: Purity, Silhouette Score, and Jaccard Index. The proposed approach achieved a Purity of 0.95, 0.91. 0.86, 0.89, the Silhouette Score was measured to be 0.5, 0.05, 0.05, 0.59, and the Jaccard Index was reported to be 0.04, 0.04, 0.05, 0.14 on Reuters, WebKB, 20 Newsgroups, and Wine datasets, respectively

关键词： Clustering algorithms Accuracy Feature extraction Semantics Partitioning algorithms Particle swarm optimization Organizations Indexes Space exploration Particle measurements optimization algorithm feature extraction PSO text processing decision making

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Dragon Boat optimization: A Meta-Heuristic for Intelligent Systems

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EXPERT SYSTEMS 2025年第2期42卷

作者： Li, Xiang Lan, Long Lahza, Husam Yang, Shaowu Wang, Shuihua Yang, Wenjing Liu, Hengzhu Zhang, Yudong Natl Univ Def Technol Coll Comp Sci & Technol Changsha Peoples R China Natl Univ Def Technol Coll Comp Sci & Technol Dept Intelligent Data Sci Changsha Peoples R China King Abdulaziz Univ Fac Comp & Informat Technol Dept Informat Technol Jeddah Saudi Arabia Xian Jiaotong Liverpool Univ Dept Biol Sci Suzhou Jiangsu Peoples R China Univ Liverpool Dept Math Sci Liverpool England Natl Univ Def Technol Key Lab Adv Microprocessor Chips & Syst Changsha Peoples R China Univ Leicester Sch Comp & Math Sci Leicester England

Dragon boat racing, a popular aquatic folklore team sport, is traditionally held during the Dragon Boat Festival. Inspired by this event, we propose a novel human-based meta-heuristic algorithm called dragon boat optimization (DBO) in this paper. It models the unique behaviours of each crew member on the dragon boat during the race by introducing social psychology mechanisms (social loafing, social incentive). Throughout this process, the focus is on the interaction and collaboration among the crew members, as well as their decision-making in various situations. During each iteration, DBO implements different state updating strategies. By accurately modelling the crew's behaviour and employing adaptive state update strategies, DBO consistently achieves high optimization performance, as validated by comprehensive testing on 29 benchmark functions and 2 structural design problems. Experimental results indicate that DBO outperforms 7 and 16 state-of-the-art meta-heuristic algorithms across these test functions and problems, respectively.

关键词： dragon boat racing human-based algorithm meta-heuristic algorithm optimization algorithm structural optimization

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