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2761
Evaluating end-to-end autonomous driving architectures: a proximal policy optimization approach in simulated environments
Published 2025-07-01“…The study uses the Proximal Policy Optimization (PPO) algorithm within the CARLA simulation environment. …”
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2762
Optimal Economic Dispatch Strategy for Cascade Hydropower Stations Considering Electric Energy and Peak Regulation Markets
Published 2025-04-01“…Specifically, firstly, the strategy adopts multi-objective optimization. The objective function takes into account the generation capacity of the cascade hydropower stations, the benefits of the EEM, the influence of the spot market, the compensatory benefits of peaking, and the sharing expenses of peaking; secondly, the constraints at the level of the power grid, the level of the cascade hydropower stations, and the level of the market are taken into account comprehensively, and the Harris Hawk Algorithm is used to solve the model; lastly, by comparing different schemes, it is observed that under varying inflow conditions, the proposed dispatch strategy in this paper yields slightly lower revenue in the EEM than other schemes. …”
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2763
Optimal scheduling of district heat pumps conceived for implementation in Energy Management Systems to participate in demand response
Published 2025-07-01“…To this end, this work proposes a novel formulation of the optimal scheduling problem of district-level HPs, conceived for EMS implementation, and based on a quadratic programming algorithm, with a specific objective function for IDR and DDR. …”
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2764
Optimization and analysis of interior permanent magnet drive motor with unequal thickness magnetic poles for electric vehicle
Published 2025-08-01“…Finally, with torque ripple, cogging torque, and output torque as optimization objectives, the particle swarm optimization algorithm was used to perform multi-objective optimization on the maximum magnetic pole thickness, minimum magnetic pole thickness, the width of magnetic pole, the depth and width of the rotor auxiliary slots, in order to determine the optimal parameters, and a prototype was then developed for experimental testing. …”
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2765
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2766
DeepGenMon: A Novel Framework for Monkeypox Classification Integrating Lightweight Attention-Based Deep Learning and a Genetic Algorithm
Published 2025-01-01“…This suggested framework leverages an attention-based convolutional neural network (CNN) and a genetic algorithm (GA) to enhance detection accuracy while optimizing the hyperparameters of the proposed model. …”
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2767
Harnessing Moderate-Sized Language Models for Reliable Patient Data Deidentification in Emergency Department Records: Algorithm Development, Validation, and Implementation Study
Published 2025-04-01“… Abstract BackgroundThe digitization of health care, facilitated by the adoption of electronic health records systems, has revolutionized data-driven medical research and patient care. While this digital transformation offers substantial benefits in health care efficiency and accessibility, it concurrently raises significant concerns over privacy and data security. …”
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2768
Grey wolf optimization technique with U-shaped and capsule networks-A novel framework for glaucoma diagnosis
Published 2025-06-01“…A hybrid segmentation method combines Grey Wolf Optimization Algorithm with U-Shaped Networks to obtain precise extraction of the optic disc regions in retinal fundus images. …”
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2769
Integrated GBR–NSGA-II Optimization Framework for Sustainable Utilization of Steel Slag in Road Base Layers
Published 2025-07-01“…Subsequently, the Gradient Boosted Regressor model was integrated into a Non-Dominated Sorting Genetic Algorithm II (NSGA-II) framework to explore optimal trade-offs between cost and emissions. …”
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2770
Enhancing MANET Security Through Federated Learning and Multiobjective Optimization: A Trust-Aware Routing Framework
Published 2024-01-01“…This study addresses these challenges by proposing FLSTMT-LAR (Federated Learning Long Short-Term Memory Trust-aware Location-aided Routing), a novel framework that integrates multiobjective optimization with LSTM-based trust prediction for robust routing decisions, implements a decentralized federated learning mechanism for collaborative trust model updates while preserving node privacy, incorporates dynamic trust assessment using LSTM networks for accurate temporal behavior pattern analysis, and provides an adaptive routing decision mechanism that effectively balances multiple performance objectives including trustworthiness, energy efficiency, and network latency. …”
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2771
Improving energy efficiency and routing reliability in wireless sensor networks using modified ant colony optimization
Published 2025-04-01“…In this study, we introduce a Modified Ant Colony Optimization Algorithm (MACOA) to address these challenges. …”
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2772
Using Surrogate Models in the Construction of a Pareto-Optimal Positioning Electropneumatic Actuator with Discrete Pneumatic Valves
Published 2025-03-01“…Sliding control was selected as a control algorithm, which effectively compensated for external disturbances and uncertainties of the system.Results. …”
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2773
Frequency regulation reserve optimization of wind-PV-storage power station considering online regulation contribution
Published 2025-06-01“…This method helps in overcoming the capacity-based reserve static setting. Finally, an optimization model was developed, along with the proposal of the linearized solving algorithm. …”
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2774
Integrated optimization and coordination of cascaded reservoir operations: Balancing flood control, sediment transport and ecosystem service
Published 2025-02-01“…To address the optimization model, an elite mutation‐based multi‐objective particle swarm optimization (MOPSO) algorithm that integrates genetic algorithms (GA) is developed. …”
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2775
Efficient optimal power flow learning: A deep reinforcement learning with physics-driven critic model
Published 2025-06-01“…To address these limitations, this paper proposes an efficient DRL algorithm with a physics-driven critic model, namely a differentiable holomorphic embedding load flow model (D-HELM). …”
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2776
Comparative analysis of forest disturbance detection in the key state-owned forest region of the Greater Khingan Range of China based on different algorithms
Published 2025-12-01“…Results showed that: (1) all three algorithms can identify the major forest disturbances with a spatial accuracy higher than 80%, and LandTrendr performed the best (OA=86.2%). (2) All three algorithms can detect the occurrence time of major disturbances with a temporal accuracy higher than 70%, and LandTrendr achieved the highest accuracy (76.4%). (3) The highest fragmentation was observed using the CCDC (184,074 disturbance patches), while LandTrendr disturbance mapping was the most complete (102,143 disturbance patches). …”
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2777
Optimized intelligent learning for groundwater quality prediction in diverse aquifers of arid and semi-arid regions of India
Published 2025-05-01“…Ensuring access to safe, affordable drinking water while implementing sustainable management practices is vital for achieving the United Nations Sustainable Development Goals-2030. …”
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2778
A novel two-stage feature selection method based on random forest and improved genetic algorithm for enhancing classification in machine learning
Published 2025-05-01“…Then, the improved genetic algorithm is used to search for the global optimal feature subset further. …”
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2779
Aircraft range fuel prediction study based on WPD with IAPO optimized BiLSTM–KAN model
Published 2025-04-01“…Additionally, the SPM chaotic mapping strategy is utilized for population initialization, while the introduction of the golden sine operator variation strategy enhances the local search capabilities of the algorithm. …”
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2780
Short-Term Prediction of Ship Heave Motion Using a PSO-Optimized CNN-LSTM Model
Published 2025-05-01“…The paper then delves into the realization method of ship heave motion based on PSO-CNN-LSTM, where the convolutional neural network (CNN) is used to extract the features of the input signal, thereby enhancing the multi-source feature fusion ability of the LSTM neural network model. The PSO algorithm is then employed to optimize the network structure and hyperparameters of the convolutional neural network. …”
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