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2381
Startup Drift Compensation of MEMS INS Based on PSO–GRNN Network
Published 2025-04-01“…The information transmission function between particle swarms was used to find the best spread parameter by iterative optimization, the particle’s position was mapped to the GRNN model, and the GRNN model was constructed with the optimal position of the swarm as the spread parameter. …”
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2382
Research on axial compensation precision puncture control method of prostate puncture robot
Published 2025-03-01“…Then, an improved adaptive particle swarm optimization (PSO) algorithm based on Levy Flight is proposed to identify parameters of this control model for puncture prostate in this article. …”
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2383
Adaptive Robust Method for Dynamic Economic Emission Dispatch Incorporating Renewable Energy and Energy Storage
Published 2018-01-01“…Moreover, an effective optimization algorithm, namely, the hybrid multiobjective Particle Swarm Optimization and Teaching Learning Based Optimization (PSO-TLBO), is employed to seek an optimal Pareto front of the proposed dispatch model. …”
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2384
Coordinated Control and Load Shifting-Based Demand Management of a Smart Microgrid Adopting Energy Internet
Published 2023-01-01“…This work provides a hybrid maximum power tracker strategy to modify the responses of standard maximum power point techniques based on particle swarm optimization-trained adaptive neuro-fuzzy inference system (ANFIS-PSO) to achieve quick and maximum solar power with minimal oscillation tracking. …”
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2385
Robust collaborative mesh networking with large-scale distributed wireless heterogeneous terminals in industrial cyber-physical systems
Published 2017-09-01“…Second, the robustness-aware collaborative mesh networking problem is formulated with a multi-objective optimization model, and an improved multi-objective particle swarm optimization algorithm based on self-adaptive evolutionary learning is exploited to search out the Pareto optimal particles with better distribution and diversity. …”
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2386
Temperature Compensation Method for MEMS Ring Gyroscope Based on PSO-TVFEMD-SE-TFPF and FTTA-LSTM
Published 2025-04-01“…This study proposes a novel parallel denoising and temperature compensation fusion algorithm for MEMS ring gyroscopes. First, the particle swarm optimization (PSO) algorithm is used to optimize the time-varying filter-based empirical mode decomposition (TVFEMD), obtaining optimal decomposition parameters. …”
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2387
Effect of Voltage Dependent Load Model on Placement and Sizing of Distributed Generator in Large Scale Distribution System
Published 2024-02-01“…In addition to AQiEA, four other algorithms (Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Grey Wolf Optimization (GWO), and Ecogeography-based Optimization (EBO) with Classification based on Multiple Association Rules (CMAR)) have also been employed for comparison. …”
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2388
Techno economic analysis of PV pumping system for rural village in East Java
Published 2024-12-01“…A comparative analysis with the Particle Swarm Optimization (PSO) algorithm indicated that QHBM excels in optimizing RF and ECO₂, whereas PSO demonstrates marginally superior performance in reducing COE. …”
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2389
Bearing fault diagnosis method based on improved compressed sensing and deep multi-kernel extreme learning machine
Published 2025-06-01“…Secongly, the compressed data was used as the input signal for the D-MKELM. Particle swarm optimization (PSO) algorithm was applied to optimize critical parameters, enabling intelligent fault diagnosis. …”
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2390
Enhancing IoT cybersecurity through lean-based hybrid feature selection and ensemble learning: A visual analytics approach to intrusion detection.
Published 2025-01-01“…In this paper, a Lean-based hybrid Intrusion Detection framework using Particle Swarm Optimization and Genetic Algorithm (PSO-GA) to select the features and Extreme Learning Machine and Bootstrap Aggregation (ELM-BA) to classify the features is introduced. …”
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2391
Development of a standardized data collection and intelligent fabric quality prediction system for the weaving department
Published 2025-01-01“…This study leverages the standardization and interoperability features of open platform communications unified architecture technology to facilitate data acquisition within the weaving department, establishing a reliable Internet of Things framework that supports subsequent fabric quality prediction, and optimizing the back propagation neural network through the K-means clustering algorithm and particle swarm optimization to predict the type and number of fabric defects. …”
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2392
Estimation of Elasticity of Porous Rock Based on Mineral Composition and Microstructure
Published 2013-01-01“…Then the support vector machine (SVM) optimized by the particle swarm optimization algorithm (PSO) is examined to generate estimations of the ECS based on the mineral composition and microstructures. …”
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2393
Cyber attack detection in IOT-WSN devices with threat intelligence using hidden and connected layer based architectures
Published 2024-12-01“…Abstract In this paper, cyber-attacks in IOT-WSN are detected through proposed optimized-Neural Network algorithms such as (i) Equilibrium Optimizer Neural Network (EO-NN), (ii) Particle Swarm Optimization (PSO-NN), (iii) Single Candidate Optimizer Neural Network (SCO-NN) and (iv) Single Candidate Optimizer Long Short-Term Memory (SCO-LSTM) with different connecting, hidden neural network layers and threat intelligence data. …”
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2394
Development of High Accuracy Classifier for the Speaker Recognition System
Published 2021-01-01“…In order to enhance noise immunity, we proposed a single hidden layer feed-forward neural network (FFNN) tuned by an optimized particle swarm optimization (OPSO) algorithm. …”
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2395
A Dynamic Processing System for Sensor Data in IoT
Published 2015-08-01“…This paper proposes a dynamic sensor data processing (SDP) system to capture and process sensor data continuously on the basis of data streaming technology. Particle Swarm Optimization (PSO) algorithm is employed to train threshold dynamically for data compression avoiding redundancy. …”
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2396
A Segmented Low-Order Bistable Stochastic Resonance Method for Fixed-Distance Target Detection in Millimeter-Wave Fuze Under Rainy Conditions
Published 2025-06-01“…To address these limitations while satisfying real-time processing requirements, this study proposes (1) a novel segmented low-order bistable stochastic resonance (SLOBSR) system based on piecewise polynomial potential functions and (2) a corresponding fixed-distance target detection algorithm incorporating signal pre-processing, particle swarm optimization (PSO)-based parameter optimization, and kurtosis threshold detection. …”
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2397
A dual-layer planning method based on improved MOPSO for distribution networks considering source–load temporal uncertainty
Published 2025-07-01“…Third, an improved multi-objective particle swarm optimization (MOPSO) algorithm with adaptive inertia weights accelerates the convergence by 25%. …”
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2398
Evaluation of a robust PID dead-time compensation controller based on the evolutionary computation method
Published 2025-10-01“…Tuning is performed by resolving an optimization issue in addition to constraints on robustness using efficient Heterogeneous Comprehensive Learning Particle Swarm Optimization (HCLPSO) evolutionary computation algorithm. …”
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2399
Zoning Elastic Modulus Inversion for High Arch Dams Based on the PSOGSA-SVM Method
Published 2019-01-01“…The zoning elastic modulus of a high arch dam is inversed by using deformation safety monitoring data in the operation period, based on the particle swarm optimization with gravitation search algorithm for support vector machine (PSOGSA-SVM) method. …”
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2400
Research on Coordinated Control of Dynamic Reactive Power Sources of DC Blocking and Commutation Failure Transient Overvoltage in New Energy Transmission
Published 2025-05-01“…A multi-objective particle swarm optimization algorithm, incorporating comprehensive trajectory sensitivity and dynamically adaptive inertia weights, is introduced, alongside Pareto front theory, to achieve rapid and balanced optimization among competing objectives. …”
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