Результаты поиска - Particle swarm optimization algorithm

  1. 1

    A Memetic Particle Swarm Optimization Algorithm for Network Vulnerability Analysis по Abadi, Mahdi, Jalili, Saeed

    Опубликовано 2011

    None

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    Электронный ресурс Глава книги
  2. 2

    Comparison of Particle Swarm Optimization Algorithms in Hyperparameter Optimization Problem of Multi Layered Perceptron по Kenta Shiomi, Tetsuya Sato, Eisuke Kita

    Опубликовано 2025-02-01

    This paper describes the application of particle swarm optimization (PSO) for the hyperparameter optimization problem of multi-layered perceptron (MLP) model. Several PSO algorithms are presented by many researchers; basic PSO, PSO with inertia weight (PSO-w), PSO with constriction factor (PSO-cf),...

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    “... This paper describes the application of particle swarm optimization (PSO) for the hyperparameter optimization problem of multi-layered perceptron (MLP) model. ...”
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  3. 3

    Applying particle swarm optimization algorithm and support vector machine for optimizing metal flow in extrusion по Gang Xu, Qiang He

    Опубликовано 2025-09-01

    Aluminum alloy profiles constitute a critical material for aviation structural components, and their die quality significantly impacts the reliability of these parts. In response to the current problems of cracking and twisting in profile quality, this study analyzes the flow characteristics of meta...

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    “...The improved support vector machine and particle swarm optimization algorithms had better recall and average accuracy than the compared algorithms, and could be applied to research on multi-objective metal extrusion process parameter optimization. ...”
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  4. 4

    WOAIP: Wireless Optimization Algorithm for Indoor Placement Based on Binary Particle Swarm Optimization (BPSO) по Omar S. Naif, Imad J. Mohammed

    Опубликовано 2022-06-01

    Optimizing the Access Point (AP) deployment has a great role in wireless applications due to the need for providing an efficient communication with low deployment costs. Quality of Service (QoS), is a major significant parameter and objective to be considered along with AP placement as well the ove...

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    “...This study proposes and investigates a multi-level optimization algorithm called Wireless Optimization Algorithm for Indoor Placement (WOAIP) based on Binary Particle Swarm Optimization (BPSO). ...”
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  5. 5

    Efficiency management of engineering projects based on particle swarm multi objective optimization algorithm по Xiu Luo, Zhouxin Yi

    Опубликовано 2025-12-01

    With the development of information technology, computer technology has been increasingly applied to management. This study aims to address problems such as low efficiency, high cost, and unstable quality in engineering project management. A research proposes an optimization method for engineering p...

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  6. 6

    Operation Optimization Strategy of Commercial Combined Electric Heating System Based on Particle Swarm Optimization Algorithm по WANG Qing, LI Congcong, WANG Pingxin, WU Qingqing, CAI Xiaoyu

    Опубликовано 2023-02-01

    In order to improve the energy efficiency of the electric heating system, a particle swarm optimization (PSO, Particle Swarm Optimization)-based operation optimization strategy for the direct storage combined electric heating system is proposed.A mathematical model of influencing factors inside a...

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    “... In order to improve the energy efficiency of the electric heating system, a particle swarm optimization (PSO, Particle Swarm Optimization)-based operation optimization strategy for the direct storage combined electric heating system is proposed.A mathematical model of influencing factors inside and outside the walls of electric heating buildings is established, and the simulink toolbox in matlab is used to build the overall system under the premise of determining the quantity of electric heating.Combining demand response ideas, the objective function is to establish the minimum heating and electricity cost of the user, and different sub-modules are selected to form the control module to achieve simulation verification, and the inverse cosine method is used to update the improved particle swarm algorithm to update the learning factor to solve the set objective function.Finally, through a calculation example of electricity consumption data of an enterprise in Jinan, Shandong, comparing energy consumption and economy can be obtained: the total energy consumption throughout the day is lower than the actual energy consumption, and the electricity bill is reduced by 17.16% compared with the unoptimized time....”
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  7. 7

    Coupling of green building construction based on particle Swarm optimizing neural network algorithm по Wang Leigang, Li Shaohua, Wang Liang, Zhang Zheng, Zhou Yuchen, Chang Long

    Опубликовано 2025-01-01

    In the continuous development of the green building industry, construction safety management faces increasing challenges, particularly in safety and environmental protection, which requires precise evaluation and control. Therefore, this study proposes a coupling analysis method for green building c...

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  8. 8

    Ultracompact Silicon Waveguide Bends Designed Using a Particle Swarm Optimization Algorithm по Po-Han Fu, Chen-Yu Chao, Ding-Wei Huang

    Опубликовано 2021-01-01

    In this study, the trajectory of a 90° bend is divided into two symmetric halves that are mirror images of each other as referenced to the symmetry axis at 45°, and each half is segmented into small curved sections. The bending radius and waveguide width for every section are p...

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    “...The bending radius and waveguide width for every section are parameters to be determined using a particle swarm optimization algorithm. The optimization is performed to maximize the transmission of the waveguide bends, which is calculated by using the three-dimensional finite-difference time-domain technique. ...”
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  9. 9

    Research on Heat Transfer Performance Prediction of Heat Exchanger Using Improved Particle Swarm Optimization Algorithm по Shuicai Qiu, Lingyan Zhang

    Опубликовано 2025-01-01

    With the increase of running time, the heat exchanger will appear dirt and even blocked, affecting the performance of the equipment. In this paper, an adaptive particle cognitive domain method is proposed. In the particle position updating method, the particle moves to the current best position with...

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    “...Using three different particle swarm optimization algorithms, namely fixed weight particle swarm optimization, linear descending weight particle swarm optimization and step mass particle swarm optimization, the heat transfer performance prediction algorithm of heat exchanger is designed according to the basic calculation principle of heat transfer performance. ...”
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  10. 10

    Harmonic oscillator based particle swarm optimization. по Yury Chernyak, Ijaz Ahamed Mohammad, Nikolas Masnicak, Matej Pivoluska, Martin Plesch

    Опубликовано 2025-01-01

    Numerical optimization techniques are widely applied across various fields of science and technology, ranging from determining the minimal energy of systems in physics and chemistry to identifying optimal routes in logistics or strategies for high-speed trading. Here, we present a novel method that...

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    “...Here, we present a novel method that integrates particle swarm optimization (PSO), a highly effective and widely used algorithm inspired by the collective behavior of bird flocks searching for food, with the physical principle of conserving energy and damping in harmonic oscillators. ...”
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  11. 11

    Phase Retrieval Utilizing Particle Swarm Optimization по Li-Jing Li, Teng-Fei Liu, Ming-Jie Sun

    Опубликовано 2018-01-01

    Phase retrieval is an important tool for image recovery techniques based on Fourier spectrum. Different iterative algorithms have been developed to retrieve phase information. However, due to the nonconvex feature of the phase optimization problem, it remains a challenge to globally obtain the optim...

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    “...In this work, we proposed an iterative algorithm to retrieve the global optimal phase information by adopting particle swarm optimization technique to the hybrid input–output scheme. ...”
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  12. 12

    The swarm intelligence algorithms and their application for the educational data analysis по Y. Yu. Dyulicheva

    Опубликовано 2019-11-01

    The purpose of the paper is the investigation of the modern approaches and prospects for the application of swarm intelligence algorithms for educational data analysis, as well as the possibility of using of ant algorithm modifications for organizing educational content in adaptive systems for condu...

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  13. 13

    A Hybrid Optimization Algorithm for the Synthesis of Sparse Array Pattern Diagrams по Youzhi Liu, Linshu Huang, Xu Xie, Huijuan Ye

    Опубликовано 2025-06-01

    To comprehensively address the challenges of aperture design, element spacing optimization, and sidelobe suppression in sparse radar array antennas, this paper proposes a hybrid particle swarm optimization (PSO) algorithm that integrates quantum-behavior mechanisms with genetic mutation. The algorit...

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  14. 14

    Air Quality Prediction Using Neural Networks with Improved Particle Swarm Optimization по Juxiang Zhu, Zhaoliang Zhang, Wei Gu, Chen Zhang, Jinghua Xu, Peng Li

    Опубликовано 2025-07-01

    Accurate prediction of Air Quality Index (AQI) concentrations remains a critical challenge in environmental monitoring and public health management due to the complex nonlinear relationships among multiple atmospheric factors. To address this challenge, we propose a novel prediction model that integ...

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  15. 15

    Interference Suppression Algorithm for Microthrust Measurement System Based on Particle Swarm Optimization Fuzzy PID по Liye Zhao, Xiaolu Xiong, Mingming Han

    Опубликовано 2025-06-01

    Micronewton thrusters have a wide range of applications in the aerospace field, and the accuracy of micronewton thrust measurement is directly affected by environmental vibration. The cantilever beam is the core part of the microthrust measurement system, and its stability directly affects the accur...

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    “...An adaptive Kalman displacement expectation estimation algorithm and a particle swarm optimization fuzzy PID microthrust system interference suppression algorithm are designed. ...”
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  16. 16

    Optimization Design of the Two-Stage Reduction Micro-Drive Mechanism Based on Particle Swarm Algorithm по Na Zhang, Dongmei Wang, Kai Li, Kaiyang Wei, Hongyu Ge, Manzhi Yang

    Опубликовано 2025-07-01

    Achieving high-precision positioning operations in a small space was of great significance in aerospace, biomedical, and other fields. In order to obtain smaller displacements with higher accuracy, this paper focused on the design, optimization, and performance analysis of a two-stage reduction micr...

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  17. 17

    Particle Swarm Optimization Based Optimal Design of Six-Phase Induction Motor for Electric Propulsion of Submarines по Lelisa Wogi, Amruth Thelkar, Tesfabirhan Shoga Tahiro, Tadele Ayana, Shabana Urooj, Samia Larguech

    Опубликовано 2022-04-01

    Recent research reveals that multi-phase motors in electric propulsion systems are highly recommended due to their improved reliability and efficiency over traditional three phase motors. This research presented a comparison of optimal model design of a six phase squirrel cage induction motor (IM) f...

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    “...This research presented a comparison of optimal model design of a six phase squirrel cage induction motor (IM) for electric propulsion by using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). ...”
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  18. 18

    Bayesian optimization with Optuna for enhanced soil nutrient prediction: a comparative study with genetic algorithm and particle swarm optimization по Bamidele A. Dada, Nnamdi I. Nwulu, Seun O. Olukanmi

    Опубликовано 2025-12-01

    Optimizing soil nutrient prediction models is important for achieving maximum agricultural output and sustainability while also ensuring effective resource management and environmental protection, as demonstrated by a case study in Johannesburg, South Africa. We implemented machine learning (ML), op...

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    “...In addition, it examines 2,000 random surface soil samples, ranging from 0 to 20 cm, that were optimized using genetic algorithms (GA), particle swarm optimization (PSO), and Optuna. ...”
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  19. 19

    Fine Tuning Hyperparameters of Deep Learning Models Using Metaheuristic Accelerated Particle Swarm Optimization Algorithm по Abdel-Hamid M. Emara, Ghada Atteia, Jawad Hasan Alkhateeb

    Опубликовано 2025-01-01

    In recent years, Convolutional Neural Networks (CNNs) have emerged as powerful tools for solving complex real-world problems, particularly in the domain of image processing. The success of CNNs can be attributed to their ability to learn hierarchical representations from data. However, achieving opt...

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