תוצאות חיפוש - Particle swarm optimization algorithm
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161
A Distributed Coalition Selection of Distribution Centers for Delivery Stations
יצא לאור 2025-01-01“...Extensive Monte Carlo simulations demonstrate that our algorithm achieves 8% higher average delivery station utility than Genetic Algorithms and 11% higher than Particle Swarm Optimization when the scale of the delivery stations is large, whereas maintaining comparable distribution center utility. ...”In modern logistics networks, an essential challenge is determining how delivery stations autonomously select the appropriate distribution center for dispatching their shipments. Traditional optimization approaches often rely on centralized decision-making and global computations, leading to high co...
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162
Design of efficient generalized digital fractional order differentiators using an improved whale optimization algorithm
יצא לאור 2025-07-01“...IWOA is developed by incorporating a piecewise linear chaotic mapping (PWLCM) and an adaptive inertia weight based on the hyperbolic tangent function (AIWHT) into the framework of original whale optimization algorithm (WOA). Simulation experiments are conducted to compare the performance of our method with that of well-known techniques, real-coded genetic algorithm (RCGA), particle swarm optimization (PSO), and original WOA. ...”This article proposes a new design and realization method for generalized digital fractional-order differentiator (GFOD) based on a composite structure of infinite impulse response (IIR) subfilters. The proposed method utilizes an improved whale optimization algorithm (IWOA) to compute the optimal c...
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163
Electric vehicle battery state of charge estimation using metaheuristic-optimized CatBoost algorithms
יצא לאור 2025-06-01“...Three distinct metaheuristic algorithms were investigated: Barnacles Mating Optimizer (BMO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Whale Optimization Algorithm (WOA), each integrated with CatBoost to optimize critical parameters including learning rate, tree depth, regularization, and bagging temperature. ...”State of Charge (SoC) estimation plays a crucial role in battery management systems for electric vehicles, directly impacting their operational efficiency and reliability. This study presents a hybrid approach combining the CatBoost algorithm with metaheuristic optimization techniques to enhance SoC...
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164
Improving and simulating urban landscape image recognition using combination optimization and fuzzy K-means algorithm
יצא לאור 2025-09-01“...The Particle Swarm Optimization (PSO) aims to efficiently find the optimal feature subset by simulating the social behavior of particles, where each particle represents a feature combination to explore and exploit the solution space. ...”Modern image recognition systems are pivotal in enhancing urban landscapes to support sustainable development and improving urban planning performance in a dynamic environment. Previous research focused on street-view panoramas is emerging as a new information source for urban studies due to the rap...
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165
Classification Prediction of Jujube Variety Based on Hyperspectral Imaging: A Comparative Study of Intelligent Optimization Algorithms
יצא לאור 2025-07-01“...This study integrates hyperspectral imaging with intelligent optimization algorithms—Zebra Optimization Algorithm (ZOA), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Grey Wolf Optimization (GWO)—and a Support Vector Machine (SVM) model to classify jujube varieties. ...”Accurate classification of jujube varieties is essential for ensuring their quality and medicinal value. Traditional methods, relying on manual detection, are inefficient and fail to meet the demands of modern production and quality control. This study integrates hyperspectral imaging with intellige...
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166
Multistep PV power forecasting using deep learning models and the reptile search algorithm
יצא לאור 2025-09-01“...Further, RSA was benchmarked against the Whale Optimization Algorithm (WOA), Gray Wolf Optimizer (GWO), and Constrained Particle Swarm Optimization (CPSO), and consistently outperformed all three across all models in both forecasting horizons. ...”Forecasting Photovoltaic (PV) power output is a key challenge in renewable energy systems, particularly for short- to mid-term operational planning. Accurate multi-step PV forecasting supports efficient energy scheduling, grid stability, and integration of solar resources. This study investigates th...
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167
Hybrid optimized data aggregation for fog computing devices in internet of things
יצא לאור 2024-05-01“...In this work, a new and novel hybrid optimization technique based on TABU Search (TS), Particle Swarm Optimization (PSO), and River Formation Dynamics (RFD) algorithms were proposed. ...”In the recent few years, the applications using Internet of Things (IoT) are becoming extremely important as they facilitate continuous and seamless interactions among humans and devices in order to improve the quality of life. With the increase in the devices used in an application for smooth and...
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168
A Thinning Method of Linear And Planar Array Antennas To Reduce SLL of Radiation Pattern By GWO And ICA Algorithms
יצא לאור 2018-12-01“...Thinning is performed using Genetic, Particle Swarm, Imperialist Competitive and Grey Wolf algorithms. ...”In the recent years, the optimization techniques using evolutionary algorithms have been widely used to solve electromagnetic problems. These algorithms use thinning the antenna arrays with the aim of reducing the complexity and thus achieving the optimal solution and decreasing the side lobe level....
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169
M-Race: A Racing Algorithm for the Tuning of Meta-Heuristics Based on Multiple Performance Objectives
יצא לאור 2025-07-01קבל טקסט מלאThe performance of meta-heuristic algorithms on optimisation problems depend on the values of control parameters. These parameters greatly influence the behaviour of algorithms and affect the quality of the solutions. In order to optimise an algorithm for a specific problem set, a structured approac...
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170
TCN-LSTM-MHSA model optimized by improved slime mould algorithm for stress prediction of roadway anchor bolts (cables)
יצא לאור 2025-05-01“...Experimental results showed that: ① Compared with the Slime Mould Algorithm (SMA), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Sparrow Search Algorithm (SSA), the ISMA optimization strategy demonstrated better convergence speed and optimization ability in multiple benchmark function tests. ② In the stress prediction experiment, ablation experiments verified the necessity of TCN, LSTM, and MHSA modules. ③ The ISMA-optimized TCN-LSTM-MHSA model outperformed mainstream prediction models such as BP and GRU in MAE, RMSE, and R2 metrics, showing higher prediction accuracy and stability....”The variation process of anchor bolt (cable) stress exhibits distinct short-term fluctuations and long-term temporal dependencies. However, traditional single prediction models have limited capability in modeling long-term trends and insufficient sensitivity to local fluctuations, often making it di...
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171
Simulation-Based Two-Stage Scheduling Optimization Method for Carrier-Based Aircraft Launch and Departure Operations
יצא לאור 2025-06-01“...To address the coupled challenges of path planning under spatial constraints and station matching/sequencing under operational constraints, we developed (1) a deep reinforcement learning (DRL)-based path planning algorithm (AAE-SAC), and (2) an enhanced particle swarm optimization (PSO) algorithm (LTA-HPSO). ...”The scheduling of carrier-based aircraft departure operations is subject to stringent temporal, spatial, and resource constraints. Conventional approaches struggle to yield exact solutions or provide a comprehensive mathematical description of this complex, dynamic process. This study proposes a sim...
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172
Optimizing Hyperspectral Desertification Monitoring Through Metaheuristic-Enhanced Wavelet Packet Noise Reduction and Feature Band Selection
יצא לאור 2025-07-01“...Using Gaofen 5B AHSI imagery as our data source, we collected spectral data for seven distinct land cover types: lush vegetation, yellow sand, white sand, saline soil, saline shell, saline soil with saline vegetation, and sandy soil. We applied Particle Swarm Optimization (PSO) to fine-tune the Wavelet Packet (WP) decomposition levels, thresholds, and wavelet basis function, ensuring optimal spectral decomposition and reconstruction. ...”Land desertification represents a significant and sensitive global ecological issue. In the Inner Mongolia region of China, soil desertification and salinization are widespread, resulting from the combined effects of extreme drought conditions and human activities. Using Gaofen 5B AHSI imagery as ou...
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173
Application of Simulated Annealing Algorithm in the Construction of Online Examination System for Tax Law Courses
יצא לאור 2025-01-01“...Experimental results demonstrate that SA achieves superior performance compared to genetic algorithms (GA), greedy approaches, ant colony optimization (ACO), and particle swarm optimization (PSO). ...”The increasing reliance on online examination systems in tax law education necessitates the development of intelligent frameworks that ensure fairness, syllabus coverage, and difficulty balance. Traditional exam construction methods, such as manual question selection and heuristic approaches, often...
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174
Structural Damage Identification Using PID-Based Search Algorithm: A Control-Theory Inspired Application
יצא לאור 2025-06-01“...The Relative Frequency Change Rate (RFCR) and Modal Assurance Criterion (MAC) were calculated as objective functions for PSA iteration; comparative studies were then conducted against Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Simulated Annealing (SA) in terms of damage identification accuracy, computational efficiency, and noise robustness. ...”This study employs a PID (Proportion, Integral, Differential)-based search algorithm (PSA) to achieve structural damage identification (SDI), localization, and quantification. We developed finite element programs for a 10-element simply supported beam, a 21-element truss, and a 7-story steel frame,...
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175
Optimized ensemble learning for non-destructive avocado ripeness classification
יצא לאור 2025-12-01“...Five machine learning models Random Forest, Decision Tree, XGBoost, Gradient Boosting, and Gaussian Mixture Model were trained separately and then merged into an ensemble. Four algorithms were used to optimize the model weight distribution: Bayesian Optimisation, Differential Evolution, Particle Swarm Optimisation, and Grid Search. ...”Classifying avocado ripeness accurately is crucial for enhancing post-harvest management and minimizing waste in agricultural supply chains. This study focuses on creating a strong ensemble classification model using spectral data from 120 kilogrammes of Buccaneer avocados obtained from the Royal Pr...
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176
Optimizing LoRaWAN Gateway Placement in Urban Environments: A Hybrid PSO-DE Algorithm Validated via HTZ Simulations
יצא לאור 2025-06-01“...This study investigates how to optimize the placement of LoRaWAN gateways by using a combination of Particle Swarm Optimization (PSO) and Differential Evolution (DE). ...”With rapid advancements in the Internet of Things (IoT), Low-Power Wide-Area Networks (LPWANs) play a crucial role in expanding IoT’s capabilities while using minimal energy. Among the various LPWAN technologies, LoRaWAN (Long-Range Wide-Area Network) is particularly notable for its capacity to enab...
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177
An Optimized Closed-Loop Z-Source Inverter for Wind Energy Generation System Using Opposition-based Sine Cosine Algorithm
יצא לאור 2024-05-01“...PI tuning for closed-loop ZSI is taken care of with the use of particle swarm optimization (PSO), the sine-cosine algorithm (SCA), and the opposition-based sine-cosine algorithm (OB-SCA). ...”For transformer-less operation, a wind energy generating system (WEGS) with an 8.5 kW wind turbine and a 6.6 kW Z-source inverter (ZSI) is modelled. A closed-loop control technique is employed at the load side of the WEGS to obtain a constant voltage with a fluctuating load at the output side of the...
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178
Optimal load frequency control system for two-area connected via AC/DC link using cuckoo search algorithm
יצא לאור 2025-06-01“...Results: The CSA was compared with particle swarm optimization algorithm (PSO) under identical conditions. ...”Background: Interconnection of different power systems has a major effect on system stability. This study aims to design an optimal load frequency control (LFC) system based on a proportional-integral (PI) controller for a two-area power system. Methods: Two areas were connected through an AC tie li...
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179
Research on path planning for mine rescue UAV based on improved Artificial Jellyfish Search algorithm
יצא לאור 2025-06-01“...UAV path planning simulation experiments showed that, when the obstacle ratio was 14.56%, compared with the Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, and JS algorithm, the IJS algorithm reduced the path planning time by 72.27%, 66.12%, and 70.87%, respectively; shortened the path length by 2.67%, 3.95%, and 1.36%, respectively; and reduced the number of turning points by 47.37%, 50%, and 28.57%, respectively. ...”To improve the path search efficiency and path optimization of mine rescue UAVs in environments with narrow passages and dense, complex obstacles, a path planning method based on the improved Artificial Jellyfish Search (IJS) algorithm was proposed. The Artificial Jellyfish Search (JS) algorithm was...
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180
Opposition-based learning techniques in metaheuristics: classification, comparison, and convergence analysis
יצא לאור 2025-07-01“...To systematically assess the effectiveness of these techniques, five widely used OBL variants—basic opposition-based learning, quasi-opposition-based learning, generalized opposition-based learning, current optimum opposition-based learning, quasi-reflection opposition-based learning—were selected for implementation within five well-established MAs: differential evolution, genetic algorithm, particle swarm optimization, artificial bee colony, and harmony search. ...”In recent years, opposition-based learning (OBL) has emerged as a powerful enhancement strategy in metaheuristic algorithms (MAs), gaining significant attention for its potential to accelerate convergence and improve solution quality. Existing research lacks a structured analysis of how different OB...
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