Showing 361 - 380 results of 2,650 for search '(((particle OR article) OR partial) OR articles) swarm optimization algorithm', query time: 0.23s Refine Results
  1. 361

    A new localization method based on improved particle swarm optimization for wireless sensor networks by Qiaohe Yang

    Published 2022-06-01
    “…However, the particle swarm diversity of the PSO algorithm is easy to lose quickly and fall into local optimal solution in the iterative process. …”
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    Article
  2. 362

    Hybrid particle swarm optimization and semi-supervised extreme learning machine for cellular network localization by Fagui Liu, Hengrui Qin, Xin Yang, Yi Yu

    Published 2017-06-01
    “…To address this problem, we propose a novel algorithm by combining particle swarm optimization and semi-supervised extreme learning machine to automatically select the optimal hyper parameters of semi-supervised extreme learning machine in this article. …”
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    Article
  3. 363

    Comprehensive Evaluation Method of Teaching Effect Based on Particle Swarm Optimization Neural Network Model by Heng Cao, Qianhui Gao

    Published 2022-01-01
    “…In view of these characteristics, this paper has conducted in-depth research to fully prove the feasibility and superiority of the content of this article. The specific summary is as follows: (1) Introduced the design concept of particle swarm optimization teaching evaluation system. (2) The use of object-oriented programming algorithms makes it easier for the algorithm to find an entry point, solve practical problems, and optimize the reusability of the algorithm method. (3) Particle swarm optimization based on quantum behavior, adjusting parameter values, the highest and the lowest, greatly reduces the difficulty of program parameter adjustment. (4) In terms of operation, it can quickly and efficiently complete the maintenance of teacher teaching information, evaluation relationship management of teacher teaching quality evaluation, evaluation content management, student evaluation, supervision evaluation, college leadership evaluation, evaluation performance management, and other operations. …”
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    Article
  4. 364

    Dynamic Deployment for Hybrid Sensor Networks Based on Potential Field-Directed Particle Swarm Optimization by Ying Zhang, Yunlong Qiao, Wei Zhao, Wei Chen, Jinde Cao

    Published 2015-09-01
    “…The proposed deployment algorithm PFPSO (Potential Field-Directed Particle Swarm Optimization) can overcome this problem and guide the mobile nodes to the optimal positions. …”
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    Article
  5. 365

    Minimum energy consumption multicast routing in ad hoc networks based on particle swarm optimization by Xiao-jian ZHU, Jun SHEN

    Published 2012-03-01
    “…In wireless ad hoc networks,because devices are powered by batteries,and multicast applications are constantly emerging,how to construct a multicast tree of the minimum energy consumption is an important problem.For the effect of the different choices of relay nodes to the construction of the minimum energy consumption multicast tree,a discrete particle swarm optimization algorithm to optimize the construction of the minimum energy consumption multicast tree was proposed.In order to avoid the premature convergence of the discrete particle swarm optimization algorithm,an inertia weight strategy was introduced to balance the global searchin ability and the local searching ability.The results of simulated experiments show that the modified discrete particle swarm optimization algorithm has strong optimization ability,and can effectively optimize the construction of the minimum energy consumption multicast tree.…”
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    Article
  6. 366

    A Mobile Robot Path Planning Method Based on Dynamic Multipopulation Particle Swarm Optimization by Yunjie Zhang, Ning Li, Yadong Chen, Zhenjian Yang, Yue Liu

    Published 2024-01-01
    “…To overcome the limitations of particle swarm optimization (PSO) in mobile robot path planning, including issues such as premature convergence and sensitivity to local optima, this study proposes a novel approach, dynamic multipopulation particle swarm optimization (DMPSO). …”
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    Article
  7. 367

    Enhancing Speech Recognition Using Improved Particle Swarm Optimization Based Hidden Markov Model by Lokesh Selvaraj, Balakrishnan Ganesan

    Published 2014-01-01
    “…In this paper a novel speech recognition method based on vector quantization and improved particle swarm optimization (IPSO) is suggested. The suggested methodology contains four stages, namely, (i) denoising, (ii) feature mining (iii), vector quantization, and (iv) IPSO based hidden Markov model (HMM) technique (IP-HMM). …”
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    Article
  8. 368

    Unified Resource Allocation and Mobility Management Technique Using Particle Swarm Optimization for VLC Networks by Muhammet Selim Demir, Sadiq M. Sait, Murat Uysal

    Published 2018-01-01
    “…In this paper, we present a unified resource allocation and mobility management algorithm based on particle swarm optimization (PSO) for indoor visible light communication (VLC) networks. …”
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    Article
  9. 369
  10. 370

    A Decomposition Model for HPLC-DAD Data Set and Its Solution by Particle Swarm Optimization by Lizhi Cui, Zhihao Ling, Josiah Poon, Simon K. Poon, Junbin Gao, Paul Kwan

    Published 2014-01-01
    “…This paper proposes a separation method, based on the model of Generalized Reference Curve Measurement and the algorithm of Particle Swarm Optimization (GRCM-PSO), for the High Performance Liquid Chromatography with Diode Array Detection (HPLC-DAD) data set. …”
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    Article
  11. 371
  12. 372

    Multi-modal prediction of breast cancer using particle swarm optimization with non-dominating sorting by Vijayalakshmi S, John A, Sunder R, Senthilkumar Mohan, Sweta Bhattacharya, Rajesh Kaluri, Guang Feng, Usman Tariq

    Published 2020-11-01
    “…The experimental results of the study are evaluated against the state-of-the-art algorithms, namely, genetic algorithm kernel density estimation and particle swarm optimization kernel density estimation wherein the results justify the superiority of the proposed model.…”
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    Article
  13. 373

    Control and Stability Analysis of Double Time-Delay Active Suspension Based on Particle Swarm Optimization by Kaiwei Wu, Chuanbo Ren

    Published 2020-01-01
    “…Aiming at the application of time-delay feedback control in vehicle active suspension systems, this paper has researched the dynamic behavior of semivehicle four-degree-of-freedom structure including an active suspension with double time-delay feedback control, focusing on analyzing the vibration response and stability of the main vibration system of the structure. The optimal objective function is established according to the amplitude-frequency characteristics of the system, and the optimal time-delay control parameters are obtained by using the particle swarm optimization algorithm. …”
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    Article
  14. 374

    Hydropower Plant Available Energy Forecasting Using Artificial Neural Network and Particle Swarm Optimization by Suriya Kaewarsa, Vanhkham Kongpaseuth

    Published 2024-10-01
    “…Considering the fluctuation and nonlinearity of data which significantly influence the forecasting results, this study develops an effective hybrid model by integrating an Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) called “PSO-ANN” model based on the hydrological and meteorological data pre-processed by cross-correlation function (CCF), autocorrelation function (AFC), and normalization techniques for predicting the available energy portion corresponding to the reservoir inflow mentioned above for a case study hydropower plant in Laos, namely, the Theun-Hinboun hydropower plant (THHP). …”
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    Article
  15. 375

    Analysis on Solar Panel Crack Detection Using Optimization Techniques by M.D. Dafny Lydia, K. Sri Sindhu, K. Gugan

    Published 2017-04-01
    “…Crack can be distinguished by utilizing optimization techniques based on segmentation. The optimization techniques are Particle Swarm Optimization (PSO), Differential Particle Swarm Optimization (DPSO) and Fractional Order Differential Particle Swarm Optimization (FODPSO). …”
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    Article
  16. 376

    Permeability Predictions for Tight Sandstone Reservoir Using Explainable Machine Learning and Particle Swarm Optimization by Jing-Jing Liu, Jian-Chao Liu

    Published 2022-01-01
    “…Based on the data preprocessing, global and local interpretations are performed according to the Shapley additive explanations (SHAP) analysis, and the redundant features in the data set are screened to identify the porosity, AC, CAL, and GR slope as the four most important features. The particle swarm optimization algorithm is then used to optimize the hyperparameters of the XGBoost model. …”
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    Article
  17. 377

    Credit card fraud Detection using Feature select method and improved machine learning algorithm by Mohammed AL-Hammadi

    Published 2025-06-01
    “…The SVM classification model then performs the final classification, with its hyperparameters optimized through the particle swarm optimization (PSO) technique. …”
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    Article
  18. 378

    Hybrid Particle Swarm and Differential Evolution Algorithm for Solving Multimode Resource-Constrained Project Scheduling Problem by Lieping Zhang, Yingxiong Luo, Yu Zhang

    Published 2015-01-01
    “…In order to find a feasible solution for the multimode resource-constrained project scheduling problem (MRCPSP), a hybrid of particle swarm optimization (PSO) and differential evolution (DE) algorithm is proposed in this paper. …”
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    Article
  19. 379

    Silicon Mode (de)Multiplexer Based on Cascaded Particle-Swarm-Optimized Counter-Tapered Couplers by Weiwei Chen, Hongxiang Li, Bohao Zhang, Pengjun Wang, Shixun Dai, Yuxiao Liu, Jun Li, Yan Li, Qiang Fu, Tingge Dai, Hui Yu, Jianyi Yang

    Published 2021-01-01
    “…In this paper, a design of a silicon mode (de)multiplexer based on cascaded counter-tapered couplers is proposed and investigated. By using the particle swarm optimization algorithm and finite difference time domain method, structural parameters of each counter-tapered coupler in our proposed mode (de)multiplexer are optimized so that high conversion efficiencies can be obtained and coupling lengths can be significantly shortened. …”
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    Article
  20. 380

    Hybrid Swarm Intelligence and Human-Inspired Optimization for Urban Drone Path Planning by Yidao Ji, Qiqi Liu, Cheng Zhou, Zhiji Han, Wei Wu

    Published 2025-03-01
    “…Urban drone applications require efficient path planning to ensure safe and optimal navigation through complex environments. Drawing inspiration from the collective intelligence of animal groups and electoral processes in human societies, this study integrates hierarchical structures and group interaction behaviors into the standard Particle Swarm Optimization algorithm. …”
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    Article