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Large-scale post-disaster user distributed coverage optimization based on multi-agent reinforcement learning
Published 2022-08-01“…In order to quickly restore emergency communication services for large-scale post-disaster users, a distributed intellicise coverage optimization architecture based on multi-agent reinforcement learning (RL) was proposed, which could address the significant differences and dynamics of communication services caused by a large number of access users, and the difficulty of expansion caused by centralized algorithms.Specifically, a distributed k-sums clustering algorithm considering service differences of users was designed in the network characterization layer, which could make each unmanned aerial vehicle base station (UAV-BS) adjust the local networking natively and simply, and obtain states of cluster center for multi-agent RL.In the trajectory control layer, multi-agent soft actor critic (MASAC) with distributed-training-distributed-execution structure was designed for UAV-BS to control trajectory as intelligent nodes.Furthermore, ensemble learning and curriculum learning were integrated to improve the stability and convergence speed of training process.The simulation results show that the proposed distributed k-sums algorithm is superior to the k-means in terms of average load efficiency and clustering balance, and MASAC based trajectory control algorithm can effectively reduce communication interruptions and improve the spectrum efficiency, which outperforms the existing RL algorithms.…”
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202
Adaptive Particle Swarm Optimization with Landscape Learning for Global Optimization and Feature Selection
Published 2025-01-01“…Particle swarm optimization (PSO), an important solving method in the field of swarm intelligence, is recognized as one of the most effective metaheuristics for addressing optimization problems. …”
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203
Impact of an improved random forest-based financial management model on the effectiveness of corporate sustainability decisions
Published 2024-12-01“…The results show that the accuracy and recall rate of the improved algorithm based on random forest proposed in this study in identifying corporate financial distress are 98.03 % and 100 % respectively. …”
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204
A Fast Fault Location Based on a New Proposed Modern Metaheuristic Optimization Algorithm
Published 2023-03-01“…Moreover, a fast and accurate modern metaheuristic optimization algorithm for this cost function is proposed, which are key parameters to estimate the fault location methods based on optimization algorithms. …”
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205
Optimizing Cloud Computing Performance With an Enhanced Dynamic Load Balancing Algorithm for Superior Task Allocation
Published 2024-01-01“…Unlike benchmark algorithms that rely on static VM selection or post-hoc relocation of cloudlets, the EDLB algorithm dynamically identifies optimal cloudlet placement in real-time. …”
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Optimal Design of Short Fiber Bragg Grating Using Bat Algorithm With Adaptive Position Update
Published 2016-01-01“…We propose a new method to optimally design short triangular-spectrum fiber Bragg gratings (TS-FBGs), using the metaheuristic bat algorithm (BA). …”
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208
An African vulture optimization algorithm based energy efficient clustering scheme in wireless sensor networks
Published 2024-12-01“…To overcome the problem of energy depletion in WSN, this paper proposes a new Energy Efficient Clustering Scheme named African Vulture Optimization Algorithm based EECS (AVOACS) using AVOA. …”
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209
The Active and Reactive Power Generation Reduction Based on Optimal location of UPFC Based on Genetic Algorithm
Published 2025-07-01“… The Unified Power Flow Controller (UPFC) is a most complex power electronic device, which can simultaneously control a local bus voltage and optimize power flows in the electrical power transmission system. …”
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210
Overlapping community-based fair influence maximization under a multi-transformation optimization algorithm
Published 2025-05-01“…Specifically, the proposed algorithm demonstrates a 9.2% improvement in average influence spread over the best existing method, while effectively addressing the trade-offs between influence, fairness, and complexity.…”
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211
Multiscale Modeling and Reconstruction of Joint Motion: Finite Element Optimization Based on Particle Swarm Algorithm
Published 2025-01-01“…Additionally, iterative reconstruction decreased the error in the knee region by approximately 30% compared to non-iterative methods. The optimization process facilitated by the particle swarm algorithm revealed that most particles achieved high fitness levels after the initial iteration, and a considerable proportion shifted to the foreground region during the second iteration once fitness values dropped below 0.2. …”
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212
Optimal Pre-disaster and Post-disaster Scheduling of Mobile Energy Storage Considering the Influence of Transportation Network
Published 2025-05-01“…Furthermore, this strategy fully accounts for traffic flow changes in the transportation network, optimizes the selection of MES scheduling paths, reduces the negative impact of traffic congestion, and further improves the scheduling efficiency of the MES. …”
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213
5G network slicing function migration mechanism based on particle swarm optimization algorithm
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214
A multi-objective optimization-based ensemble neural network wind speed prediction model
Published 2025-09-01“…Built upon the NSGA-II framework, NS-ADPOA enhances offspring generation by leveraging a probabilistic error-driven fusion of Particle Swarm Optimization (PSO) and Whale Optimization Algorithm (WOA), combining their strengths in local and global search, respectively. …”
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215
Leveraging Radiomics and Genetic Algorithms to Improve Lung Infection Diagnosis in X-Ray Images Using Machine Learning
Published 2024-01-01“…A comparative analysis is conducted among the genetic algorithm-based TPOT (Tree-based Pipeline Optimization Tool) settings, namely TPOT-Default, TPOT-Light, and TPOT-Sparse, to select the most effective hyperparameters. …”
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216
Prediction of Interest Rate Using Artificial Neural Network and Novel Meta-Heuristic Algorithms
Published 2021-03-01“…The main goal of this article, as it is clear from the title, is the prediction of interest rate using ANN and improving the network using some novel heuristic algorithms such as Moth Flame Optimization algorithm (MFO), Chimp Optimization Algorithm (CHOA), Time-varying Correlation Particle Swarm Optimization algorithm (TVAC-PSO), etc. we used 17 variables such as oil price, gold coin price, house price, etc. as input variables. …”
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Reflective Distributed Denial of Service Detection: A Novel Model Utilizing Binary Particle Swarm Optimization—Simulated Annealing for Feature Selection and Gray Wolf Optimization-...
Published 2024-09-01“…The BPSO-SA algorithm enhances the global search capability of Particle Swarm Optimization (PSO) using the SA mechanism and effectively screens out the optimal feature subset; the GWO algorithm optimizes the hyperparameters of LightGBM by simulating the group hunting behavior of gray wolves to enhance the detection performance of the model. …”
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219
Magnetic targets positioning method based on multi-strategy improved Grey Wolf optimizer
Published 2025-05-01“…Therefore, a Multi-Strategy Improved Grey Wolf Optimizer (MSIGWO) algorithm has been proposed to enhance the accuracy of magnetic target state estimation. …”
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220
Optimizing Assembly Error Reduction in Wind Turbine Gearboxes Using Parallel Assembly Sequence Planning and Hybrid Particle Swarm-Bacteria Foraging Optimization Algorithm
Published 2025-07-01“…The methodology results in a 38% reduction in total assembly errors, improving both process accuracy and efficiency. Specifically, the PSBFO algorithm reduced errors from an initial value of 50 to a final value of 5 across 20 iterations, with components such as the low-speed shaft and planetary gear system showing the most substantial reductions. …”
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