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2421
A Generalized Shape Function for Vibration Suppression Analysis of Acoustic Black Hole Beams Based on Fractional Calculus Theory
Published 2025-03-01“…To obtain the best parameters of the shape function under various parameters, the Particle Swarm Optimization (PSO) algorithm is employed. …”
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2422
A Robust Enhanced Ensemble Learning Method for Breast Cancer Data Diagnosis on Imbalanced Data
Published 2024-01-01“…In addition, a data-driven based particle swarm optimization algorithm automatically is used to select the value of parameters for base classifiers. …”
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2423
Electric Vehicle Charging Load Forecasting Based on K-Means++-GRU-KSVR
Published 2024-12-01“…Then, a combination of kernel support vector regression (KSVR) and gated recurrent unit (GRU) models was used to handle nonlinear features and time-dependent data, where particle swarm optimization (PSO) further optimized the model parameters to improve the forecasting accuracy. …”
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2424
A Novel Energy Consumption Prediction Model Integrating Real-Time Traffic State Recognition and Velocity Prediction of BEVs
Published 2024-01-01“…In the energy consumption prediction stage, a particle swarm optimization-radial basis function neural network (PSO-RBFNN) model is employed to estimation the energy consumption. …”
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2425
Distribution Network Differential Protection Technology Based on 5G Communication and Improved DTW
Published 2023-08-01“…To solve the problem of communication delay and delay jitter, an improved dynamic time programming (DTW) algorithm was introduced. Aiming at the shortcomings of traditional DTW algorithms, such as large overhead, algorithm accuracy and efficiency limited by sequence amplitude difference, and empirical selection of parameters, the global path constraint strategy, data standardization strategy and particle swarm optimization strategy are proposed to be improved. …”
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2426
Combination of Feature Selection and Learning Methods for IoT Data Fusion
Published 2017-12-01“…In this paper, we propose five data fusion schemes for the Internet of Things (IoT) scenario,which are Relief and Perceptron (Re-P), Relief and Genetic Algorithm Particle Swarm Optimization (Re-GAPSO), Genetic Algorithm and Artificial Neural Network (GA-ANN), Rough and Perceptron (Ro-P)and Rough and GAPSO (Ro-GAPSO). …”
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2427
A novel hybrid model for predicting the bearing capacity of piles
Published 2024-10-01“…The main objective of this study is to propose a hybrid model coupling least squares support vector machine (LSSVM) with an improved particle swarm optimization (IPSO) algorithm for the prediction of bearing capacity of piles. …”
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2428
Artificial Seismic Source Field Research on the Impact of the Number and Layout of Stations on the Microseismic Location Error of Mines
Published 2019-01-01“…Moreover, the impact of wave velocity, velocity-free location algorithm, and position of the seismic source on the microseismic location error of mines is discussed by establishing the ideal theoretical model of the wave velocity location and with particle swarm optimization. …”
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2429
Machine learning-based forecasting of ground surface settlement induced by metro shield tunneling construction
Published 2024-12-01“…This study collects multi-point surface settlement data from monitoring sections and proposes a data preprocessing method based on tangent circles to transform discrete monitored data into continuous and smooth data. On this basis, the Particle Swarm Optimization (PSO) algorithm is employed to optimize a Back Propagation Neural Network(BPNN) for the subsequent prediction of ground surface settlement. …”
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2430
Improved Variational Mode Decomposition in Pipeline Leakage Detection at the Oil Gas Chemical Terminals Based on Distributed Optical Fiber Acoustic Sensing System
Published 2025-03-01“…This paper employs a distributed fiber optic sensing system to collect pipeline leakage signals and processes these signals using the traditional variational mode decomposition (VMD) algorithm. While traditional VMD methods require manual parameter setting, which can lead to suboptimal decomposition results if parameters are incorrectly chosen, our proposed method introduces an improved particle swarm optimization algorithm to automatically determine the optimal parameters. …”
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2431
Resource Management Based on Security Satisfaction Ratio with Fairness-Aware in Two-Way Relay Networks
Published 2015-07-01“…We model the security resource management problem as a mixed integer programming problem, which is decomposed into three subproblems, distributed power allocation, distributed subchannel allocation, and distributed subchannel pairing, and then solved it in constraint particle swarm optimization (CPSO), binary CPSO (B_CPSO), and classic Hungarian algorithm (CHA) method, respectively. …”
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2432
Generalizability of machine learning models for diabetes detection a study with nordic islet transplant and PIMA datasets
Published 2025-02-01“…Researchers utilizing a hybrid feature extraction method such as Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) followed by metaheuristic feature selection algorithms as Harmonic Search (HS), Dragonfly Algorithm (DFA), Elephant Herding Algorithm (EHA). …”
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2433
A Novel Hermite Interpolation-Based MPPT Technique for Photovoltaic Systems Under Partial Shading Conditions
Published 2024-01-01“…The feasibility and effectiveness of the proposed HPO algorithm are validated through a comparison with INC and Particle Swarm Optimization (PSO) methods. …”
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2434
A Two-Stage Site Selection and Capacity Determination Method for Energy Storage Power Stations Based on HC-MOPSO
Published 2024-12-01“…A planning method for energy storage stations based on Hierarchical Clustering (HC) and Multi Objective Particle Swarm Optimization (MOPSO) is proposed to address the difficulty of balancing the coupling effects of active power and node voltage in large-scale energy storage planning. …”
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2435
Augmented robustness in home demand prediction: Integrating statistical loss function with enhanced cross-validation in machine learning hyperparameter optimisation
Published 2025-09-01“…Using three evolutionary algorithms Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Differential Evolution (DE) we optimize two ensemble models: XGBoost and LightGBM. …”
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2436
Secure intelligent reflecting surface assisted mobile edge computing system with wireless power transfer
Published 2024-12-01“…Moreover, we propose a dichotomy particle swarm algorithm based on the bisection method to process the overall optimization problem and improve the convergence speed. …”
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2437
Novel hybrid model to improve the monthly streamflow prediction: Integrating ANN and PSO
Published 2023-08-01“…This study invented a novel approach for the monthly water streamflow of the Tigris River in Amarah City, Iraq, by integrating an artificial neural network (ANN) with the particle swarm optimisation algorithm (PSO), depending on data preprocessing. …”
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2438
Computational Adaptive Optics for HAR Hybrid Trench Array Topography Measurement by Utilizing Coherence Scanning Interferometry
Published 2025-06-01“…Here, we propose a computational aberration correction method for measuring the topography of the HAR structure by the particle swarm optimization (PSO) algorithm without constructing a database and prior knowledge, and a phase filter in the spatial frequency domain is constructed to restore interference signals distorted by shift-variant aberrations. …”
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2439
Tactical Coordination-Based Decision Making for Unmanned Combat Aerial Vehicles Maneuvering in Within-Visual-Range Air Combat
Published 2025-02-01“…Finally, an improved particle swarm optimization algorithm (I-PSO) is proposed, which enhances the optimization ability and real-time performance through the design of local social factor iterative components and adaptive adjustment of inertia weights. …”
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2440
An improved deep CNN-based freshwater fish classification with cascaded bio-inspired networks
Published 2025-04-01“…Initially comprising eight classes, the dataset undergoes feature extraction using CNN algorithms, followed by the utilization of various feature selection methods such as Support Vector Classifier, Principal Component Analysis, Linear Discriminant Analysis, and optimization models like Particle Swarm Optimization, Bacterial Foraging Optimization, and Cat Swarm Optimization. …”
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