-
621
Efficient Iris Recognition Based on Optimal Subfeature Selection and Weighted Subregion Fusion
Published 2014-01-01“…Thirdly, to make matching more effective, this paper proposes a novel matching method based on weighted sub-region matching fusion. Particle swarm optimization is utilized to accelerate achieve different sub-region’s weights and then weighted different subregions’ matching scores to generate the final decision. …”
Get full text
Article -
622
PAPR Reduction Using Fireworks Search Optimization Algorithm in MIMO-OFDM Systems
Published 2018-01-01“…Moreover, it turns out from the results that the proposed PTS scheme-based FWA clearly outperforms the hottest and most important evolutionary algorithm in the literature like simulated annealing (SA), particle swarm optimization (PSO), and genetic algorithm (GA).…”
Get full text
Article -
623
A Fault Diagnosis Method for Rolling Bearings Based on Feature Fusion of Multifractal Detrended Fluctuation Analysis and Alpha Stable Distribution
Published 2016-01-01“…Thirdly, the KPCFFs served as the input of Least Squares Support Vectors Machine (LSSVM) based on Particle Swarm Optimization (PSO) to assess rolling bearings’ fault position and damage severity. …”
Get full text
Article -
624
Deep Learning-Based Energy Consumption Prediction Model for Green Industrial Parks
Published 2025-12-01“…These components are then predicted using a multi-factor LSTM model optimized by improved particle swarm optimization, with the results aggregated for the final forecast. …”
Get full text
Article -
625
A Multiswarm Intelligence Algorithm for Expensive Bound Constrained Optimization Problems
Published 2021-01-01“…All these developed algorithms have some merits and also demerits. Particle swarm optimization (PSO), firefly algorithm, ant colony optimization (ACO), and bat algorithm (BA) have gained much popularity and they have successfully tackled various test suites of benchmark functions and real-world problems. …”
Get full text
Article -
626
Shallow Foundation Settlement Quantification: Application of Hybridized Adaptive Neuro-Fuzzy Inference System Model
Published 2020-01-01“…This research emphasis on the implementation of newly developed machine learning models called hybridized Adaptive Neuro-Fuzzy Inference System (ANFIS) with Particle Swarm Optimization (PSO) algorithm, Ant Colony optimizer (ACO), Differential Evolution (DE), and Genetic Algorithm (GA) as efficient approaches to predict settlement of shallow foundation over cohesion soil properties. …”
Get full text
Article -
627
Performance evaluation of an optimized simplified nonlinear active disturbance rejection controller for rotor current control of DFIG-based wind energy system
Published 2025-02-01“…To address these challenges, an optimized simplified nonlinear active disturbance rejection (SNADR) control strategy, enhanced through the Particle Swarm Optimization (PSO) algorithm for parameter tuning, is proposed. …”
Get full text
Article -
628
Modeling and Solving Multi-Objective Path Planning Problem for Cooperative Cable-Suspended Load Transportation Considering the Time Variable Risk
Published 2025-01-01“…In addition, we propose an improved hybrid fuzzy particle swarm optimization (PSO) and whale optimization algorithm (WOA) to solve the introduced path planning problem efficiently. …”
Get full text
Article -
629
Identification of Vibration Signal for Residual Pressure Utilization Hydraulic Unit Using MRFO-BP Neural Network
Published 2022-01-01“…Compared with Particle Swarm Optimization-BP (PSO-BP) neural network, Bat Algorithm-BP (BA-BP) neural network, and BP neural network, the results show that the identification rate of each measuring point from the MRFO-BP neural network is greatly improved. …”
Get full text
Article -
630
Ship-Borne Phased Array Radar Using GA Based Adaptive α-β-γ Filter for Beamforming Compensation and Air Target Tracking
Published 2015-01-01“…The genetic algorithm (GA) and the particle swarm optimization (PSO) methods are applied to estimate the gain parameters of adaptive α-β-γ filters, while achieving the optimum objective of minimum root mean square error (RMSE). …”
Get full text
Article -
631
Advanced machine learning approach with dynamic kernel weighting for accurate electrical load forecasting
Published 2025-01-01“…The first step in preparing the dataset is to perform preprocessing, which involves conducting correlation analysis, scaling, and normalization followed by initial hyperparameter tuning using the multiswarm Levy flight particle swarm optimization technique. Compared with traditional methods, EDW-MKSVR offers greater adaptability to shifting load patterns since it makes use of dynamic kernel weight modifications that are dependent on data attributes. …”
Get full text
Article -
632
Fault Diagnosis of Piezoelectric Sensor Patches for Vibration Control Based on Multifeature Fusion and Improved SVM
Published 2019-01-01“…In order to improve the accuracy of fault self-diagnosis of piezoelectric sensor patches, singular value decomposition (SVD) and Hilbert marginal spectrum method are proposed to extract multiple features of each IMF component and conduct feature fusion, and a support vector machine (SVM) based on particle swarm optimization (PSO) is designed for fault identification of different eigenvalues. …”
Get full text
Article -
633
Bivariate Stochastic Optimization Model for Bidding Strategies Considering Competition Among Renewable Power Producers
Published 2024-01-01“…Then, the Newton method and particle swarm optimization (PSO) are combined to solve the BSO model in which various probability distribution functions (PDFs) of renewable energy generation are considered. …”
Get full text
Article -
634
Using crafted features and polar bear optimization algorithm for short-term electric load forecast system
Published 2025-01-01“…PBO was compared with commonly used optimization algorithms like particle swarm optimization (PSO) and genetic algorithm (GA). …”
Get full text
Article -
635
Power Prioritization and Load Shedding in an Island with RESs Using ABC Algorithm
Published 2020-01-01“…The results are then compared with those of Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and GA-PSO hybrid. Both generation and overload contingencies are considered on a standard IEEE 30-bus system on a MATLAB platform. …”
Get full text
Article -
636
Parameter Optimization Study of Gas Hydrate Reservoir Development Based on a Surrogate Model Assisted Particle Swarm Algorithm
Published 2022-01-01“…Firstly, an improved surrogate model assisted particle swarm optimization (PSO) algorithm was proposed in this paper. …”
Get full text
Article -
637
PID CONTROLLER FOR SPEED CONTROL OF PMSM BASED ON MAYFLY OPTIMIZATION ALGORITHM
Published 2025-02-01“…This suggested approach has been verified with MATLAB, and the outcomes are compared with the standard particle swarm optimization technique (PSO) and conventional PID. …”
Get full text
Article -
638
Runoff Prediction and Uncertainty Analysis for Xijiang River Basin Based on CMIP6 Climate Scenarios
Published 2025-01-01“…Based on this, the Xin'anjiang hydrological model (XAJ) is built, and the particle swarm optimization (PSO) algorithm is employed to calibrate and validate the model parameters. …”
Get full text
Article -
639
Joint Optimization of Berths and Quay Cranes Considering Carbon Emissions: A Case Study of a Container Terminal in China
Published 2025-01-01“…This study presents an integrated model that incorporates tidal factors into the joint optimization of berth and quay crane operations, addressing both service standards and emissions during port stays and crane activities, and further designs a PSO-GA hybrid algorithm, combining particle swarm optimization (PSO) with crossover and mutation operators from a genetic algorithm (GA), to enhance optimization accuracy and efficiency. …”
Get full text
Article -
640
Multiobjective Optimization Design and Experimental Study of Desulfurization Dust Removal Centrifugal Pump Based on Immune Particle Swarm Algorithm
Published 2018-01-01“…The immune particle swarm optimization algorithm was used to optimize the multiobjective function, and the optimal combination of the main parameters was obtained. …”
Get full text
Article