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2nd RSI/ISM International Conference on Robotics and Mechatronics (ICRoM)

作者： Zafari, Nasim Ghesemi, Mohammad Hasan Shahid Chamran Univ Technol Sch Mech Engn Ahvaz Iran Babol Noshirvani Univ Technol Sch Mech Engn Babol Sar Iran

ISBN: (纸本)9781479967438

Designing of stable time optimal path for bipeds is one of the main issues in motion of bipeds. Motion parameters such as participation of motion phases and the distance between hip joint and ankle joint of support leg at the beginning and the end of the single support phase, have important effect in designing of time optimal path. In this paper the effect of these two motion parameters on time optimal path is discussed. At first, time optimal path is designed by particle swarm optimization algorithm considering definite participation of double support phase and actuators torque limitation. To ensure Stability, motion of a biped needs to follow specific pattern to comply with certain stability criterion such as zero moment point. Then the effect of double support phase on time optimal path and torque limitation on participation of the double support phase which satisfies time optimal path are studied. Finally effect of distance between hip joint and ankle joint of support leg at the beginning and the end of the single support phase on time optimal path is investigated.

关键词： biped robot motion parameters time optimal path pso algorithm

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Cloud Computing Resource Schedule Strategy Based on pso algorithm

Cloud Computing Resource Schedule Strategy Based on PSO Algo...

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International Conference on Advances in Materials Science and Information Technologies in Industry (AMSITI)

作者： Xiong, Yingyidu Wu, Yanyan Ningbo DaHongYing Univ Ningbo Zhejiang Peoples R China

ISBN: (纸本)9783038350125

Resource schedule Strategy is the core technology of cloud computing. pso algorithm is one of dynamic adaptation resource scheduling algorithms to cloud computing. The virtual machines and the hosts can be scheduled reasonable by adjusting parameters. The resource can be scheduled quickly because of the dynamic trend calculation of pso algorithm, to ensure real-time of the Cloud Calculation.

关键词： Cloud computing Resource scheduling pso algorithm

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Evolving Interest Based User Groups Using pso algorithm 4

Evolving Interest Based User Groups Using PSO algorithm

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International Conference on Recent Trends in Information Technology

作者： Ganesan, Sumathi Sivaneri, Arul Isai Udhaya Selvaraju, SendhilKumar Anna Univ CEG Dept IST Chennai Tamil Nadu India

ISBN: (纸本)9781479949892

Any Web site may have the continuous improvement based on the getting information of the users' needs. There is a step to achieve it by the collection of users' search data and analysis of those data. The swarm intelligence technique of Particle Swarm Optimization(pso) is applied for evolving similar user groups. pso is important to identify the web users' travels with the same interests. The data set comprises of web log files obtained by collecting the user logs during a six month period. The pso algorithm is attempted for user categorization. In web search, the users are grouped into different categories based on their similar travels. The grouping performance of the pso technique is compared with the techniques of DBSCAN and Kmeans.

关键词： Web Usage Mining ODP taxonomy Clustering pso algorithm

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On the Deployment Problem of Multiple Drones in Millimeter Wave Systems

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JOURNAL OF NETWORK AND SYSTEMS MANAGEMENT 2024年第4期32卷 71-71页

作者： Shakhatreh, Hazim Al-Dagamseh, Wa'ed Albasheer, Samah Bani-Hani, Khaled Hayajneh, Khaled Yarmouk Univ Hijjawi Fac Engn Technol Dept Telecommun Engn Irbid 21163 Jordan Amer Univ Middle East Coll Engn & Technol Egaila 54200 Kuwait

Millimeter wave (mm-Wave) frequency bands have paved the way for wide drone applications to support future wireless networks. This research studies the integration of drone-assisted wireless networks with 5G mm-Wave communications. Two scenarios are considered: the single and multiple drone scenarios. In the first scenario, we aim to find an effective 3D positioning of a single drone that minimizes the overall transmit power required to serve the users. Therefore, we utilize the particle swarm optimization (pso) algorithm to solve the optimization problem. In the second scenario, a drone's low transmission power may be inefficient in utilizing a single drone to cover a set of users. To that end, we aim to minimize the number of drones and find efficient 3D placements for the drones required to serve the users. Minimizing the number of drones will reduce operational costs during drones' wireless network planning and operations. Moreover, it helps operators utilize unused drones to extend wireless coverage. Therefore, we propose the clustering algorithm to solve this optimization problem. Finally, the results of simulations are used to verify the efficacy of the suggested algorithms in our scenarios.

关键词： Drones Millimeter wave communications 5G and beyond wireless applications pso algorithm K-means clustering algorithm

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3D position deployment and performance optimization of mmWave UAV-assisted HetIoT under jamming condition

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COMPUTER NETWORKS 2024年 248卷

作者： Wei, Xingchen Peng, Laixian Xu, Renhui Li, Aijing Yu, Xingyue Wang, Hai Army Engn Univ PLA Coll Commun Engn Nanjing 210007 Peoples R China

Heterogeneous Internet of Things (HetIoT) has received widespread attention due to its provision of various convenient services in fields such as smart cities, intelligent transportation, environmental monitoring and security systems. Due to HetIoT inherently demands high data rates, bandwidth, and low latency, the application of millimeter-wave (mmWave) unmanned aerial vehicle (UAV) as emergency aerial base station (ABS) providing services to HetIoT users has become a low-cost and efficient means. However, due to the sensitivity of mmWave to obstacles and jamming, guaranteeing network performance has become a pressing issue. This paper considers a mmWave UAV-assisted HetIoT under jamming conditions, where auxiliary ABSs serve multiple ground users (GUs) who generate a large amount of sensor data. We establish a coverage maximization problem under the constraints of signal-to-interference ratio (SIR) threshold, maximum power of ABSs and maximum number of GUs that the base station can serve, and propose a novel ABS hovering deployment algorithm M-HiApso that combines the artificial potential field (APF) method and the improved particle swarm optimization (pso) algorithm in a hierarchical manner. Specifically, the multi-element APF method is used to characterize the horizontal force between nodes, combined with the improved hierarchical adaptive pso algorithm to adjust the horizontal position of the ABS to obtain the optimal UAV hovering position and power allocation strategy. Numerical results show that the coverage rate reached 96.2% when the number of iterations was 283, and it can reach up to 99.6%.

关键词： HetIoT Jamming condition mmWave UAV-assisted network Artificial potential field pso algorithm

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Mars Probe Landing Control Scheme Based on Dynamic Programming and Lion Swarm algorithm 22

Mars Probe Landing Control Scheme Based on Dynamic Programmi...

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6th International Conference on Virtual and Augmented Reality Simulations (ICVARS)

作者： Gao, Shengkun Zhang, Tianyu Wuhan Univ Technol Sch Automat Wuhan Peoples R China

ISBN: (纸本)9781450387330

The success of Tianwen No. 1 mission is a landmark achievement of independent innovation and leapfrog development of China's aerospace industry. In this paper, a differential equation model based on Newton ' s second law and pulse theorem is established for the landing control problem of Tianwen-1 Mars probe. The fourth-order Runge-Kutta method and the lion swarm optimization algorithm are used to solve the shortest landing time of the probe, and the shortest landing time is calculated to be 7.1 min. At the same time, the control functions of the engine in the aerodynamic deceleration stage, parachute control stage and dynamic deceleration stage are simulated, and the shortest time-consuming scheme of the detector landing process is determined. When the life of the detector is fixed, this study can shorten the landing time and enter the working state as soon as possible, which can prolong the working time of the detector. To a certain extent, it makes up for the deficiency of the research on the landing time planning of the detector, has certain innovation, and promotes the further development of China ' s aerospace industry to a certain extent. At the same time, it provides some method reference and experience guidance for the shortest time of kinematic path planning in real life.

关键词： Martian probe Dynamic optimization Fourth-order Runge-Kutta method pso algorithm

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Estimating collapse risk and reliability of concrete moment frame structure using response surface method and hybrid of artificial neural network with particle swarm optimization algorithm

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART O-JOURNAL OF RISK AND RELIABILITY 2021年第6期235卷 1072-1089页

作者： Bayari, Mohammad Amin Shabakhty, Naser Izadi Zaman Abadi, Esmaeel Islamic Azad Univ Najafabad Branch Dept Civil Engn Najafabad *** Iran Iran Univ Sci & Technol Sch Civil Engn Tehran Iran

Structural collapse performance assessment has been at the center of many researchers' interest due to complications of this phenomenon and uncertainties involved in modeling the simulation of the structural collapse response. This research aims to predict the structural collapse responses including mean collapse capacity, collapse standard deviation, and collapse drift by considering modeling uncertainties and then estimating collapse fragility curves, collapse risk, and reliability using Response Surface Method (RSM) and Artificial Neural Network (ANN). Modeling uncertainties for evaluating collapse responses are the parameters of the modified Ibarra-Krawinkler moment-rotation curve. Moreover, to analyze the structural uncertainty, the correlation between the model parameters in one component and between two structural components was considered. The Latin Hypercube Sampling (LHS) method and Cholesky decomposition were used to produce independent and dependent random variables, respectively. To predict the collapse responses of the structure, taking into account the uncertainties, as the number of uncertainties increases, the number of simulations for the uncertainties also increases, leading to a significant increase in the computational effort to estimate the structural responses, in the presence of a limited number of samples for uncertainties, a hybrid of ANN with pso algorithm was used to reduce the computational effort in order to estimate the collapse fragility curves, collapse risk, and structural reliability. The results show that structural collapse responses can be predicted with appropriate accuracy by producing a limited number of samples for uncertainties and using an ANN-pso algorithm.

关键词： Collapse responses risk and reliability uncertainty response surface method artificial neural network pso algorithm

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Memristor-based input delay reservoir computing system for temporal signal prediction

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MICROELECTRONIC ENGINEERING 2024年 293卷

作者： Lu, Zhen-Ni Ye, Jing-Ting Zhang, Zhong-Da Cai, Jia-Wei Pan, Xiang-Yu Xu, Jian-Long Gao, Xu Zhong, Ya-Nan Wang, Sui-Dong Soochow Univ Inst Funct Nano & Soft Mat FUNSOM Jiangsu Key Lab Carbon Based Funct Mat & Devices Suzhou 215123 Jiangsu Peoples R China Macau Univ Sci & Technol Macao Inst Mat Sci & Engn MIMSE MUST SUDA Joint Res Ctr Adv Funct Mat Taipa 999078 Macao Peoples R China

Reservoir computing (RC) system, featured by its recursive structure, has been utilized for temporal signal processing, offering both low power consumption and high computational speed. This work reports on a novel input delay reservoir computing (ID-RC) system based on the oxide memristors, which can be applied to temporal signal prediction. The particle swarm optimization (pso) algorithm is employed in the ID-RC system to obtain optimal hyperparameters for multi-step prediction in the Mackey-Glass task, with a normalized rootmean-square error (NRMSE) of only 0.09 at the 20th step. Significantly, by employing the ID-RC system in temporal signal prediction of the He non map and the nonlinear autoregressive moving average (NARMA10), small NRMSEs of 0.047 and 0.017 were achieved, respectively. The memristor-based ID-RC system turns out to be highly promising in forecasting of chaotic time series.

关键词： Memristor IGZO Reservoir computing pso algorithm Temporal signal prediction

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A fast, non-invasive calibration method for optical switching delay line based on particle swarm optimization algorithm

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OPTICS AND LASER TECHNOLOGY 2024年 179卷

作者： Niu, Hongsheng Shi, Shangqing Chen, Yifei Wang, Jin Wang, Qichao Guo, Chen Cheng, Wei Wang, Pengfei Hu, Guohua Cui, Yiping Yun, Binfeng Southeast Univ Adv Photon Ctr Sch Elect Sci & Engn Nanjing 210096 Peoples R China

Optical tunable delay line (OTDL) is playing an increasingly significant role in microwave photonic technology. As a representative OTDL, optical switching delay line (OSDL) based on cascaded optical switches has become widespread due to its advantages of large bandwidth, high delay accuracy, and easy control. However, due to fabrication errors, the "through" and "cross" states of all the optical switches in the OSDL must be calibrated by inserting additional components for monitoring, which will inevitably increase the chip size and cost. Therefore, achieving simple and non-invasive calibration of OSDL is very important. Here we proposed a fast and noninvasive calibration method based on spectrum analysis accelerated by particle swarm optimization algorithm (pso). As a proof-of-concept, we accurately calibrated a 5-Bit silicon OSDL chip by using the proposed method and measured all the delay states and transmission spectra of the OSDL. The results are in good agreement with those obtained by the traditional calibration method with additional optical power monitoring taps.

关键词： Mach-Zehnder interference Optical switching delay line Non-invasive calibration pso algorithm

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Geometry-force interactive design and optimization method of cable dome structures

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THIN-WALLED STRUCTURES 2024年 200卷

作者： Xue, Suduo Li, Xuanzhi Li, Xiongyan Beijing Univ Technol Minist Educ Key Lab Urban Secur & Disaster Engn 100 Pingleyuan Beijing Peoples R China

Cable dome is a typical flexible structural system. Its initial geometry determines the prestress distribution and affects the structural performance. Using geometric parameters to establish the mechanical equation of initial state can effectively realize the geometric-force interactive design and optimization of cable dome structure. Consequently, a standardized equation is established in this paper to uniformly express the geometric-force relationship, utilizing a feasible prestress distribution function expressed by geometric parameters. Subsequently, an interactive design method for initial geometry and prestress is presented. The proposed method is theoretically expounded in terms of geometric design, prestress design and shape optimization. Two typical cable dome cases, Geiger and Levy, are successfully applied to accomplish the geometric-force design and optimization of the initial state. The results show that the efficient design of initial state can be completed by establishing the interaction between geometry and force without repeated algebraic calculation. The optimized initial geometry can significantly improve the Structural stiffness.

关键词： Cable dome Geometry design Prestress design Shape optimization pso algorithm

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