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Modeling the prediction of spontaneous rupture and bleeding in hepatocellular carcinoma via machine learning algorithms
Published 2025-07-01“…Abstract This study aimed to identify the risk factors associated with spontaneous rupture and bleeding in hepatocellular carcinoma, establish a prediction model for spontaneous rupture bleeding via a machine learning algorithm, and validate and evaluate the predictive efficacy of the model. …”
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1602
A levy chaotic horizontal vertical crossover based artificial hummingbird algorithm for precise PEMFC parameter estimation
Published 2024-11-01“…The combination of this method with PEMFC parameters results in a significantly improved performance compared to traditional methods, such as Particle Swarm Optimization (PSO), Differential Evolution (DE), Grey Wolf Optimizer (GWO), and Sparrow Search Algorithm (SSA), which we use as baselines to validate PEMFC parameters. …”
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1603
Predictive modelling of aquaculture water quality using IoT and advanced machine learning algorithms
Published 2025-07-01Get full text
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1604
Model-Free Attitude Control of Spacecraft Based on PID-Guide TD3 Algorithm
Published 2020-01-01“…Aiming at this problem, the PID-Guide TD3 algorithm is proposed, which can speed up the training speed and improve the convergence precision of the TD3 algorithm. …”
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1605
Big Data and AI Algorithms for Sustainable Development Goals: A Topic Modeling Analysis
Published 2024-01-01“…AI applications notably improve healthcare by advancing disease tracking, tailored treatments, and precision medicine, fostering universal healthcare and reducing noncommunicable disease mortality. …”
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1606
Soft detection model of corrosion leakage risk based on KNN and random forest algorithms
Published 2024-09-01“…Future research efforts should focus on enhancing data acquisition and analysis techniques, optimizing the model structure, and improving the model adaptability and accuracy across various application scenarios.…”
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Metaheuristic Optimization of Wind Turbine Airfoils with Maximum-Thickness and Angle-of-Attack Constraints
Published 2024-12-01“…The drag and lift coefficients are estimated, and a metaheuristic optimization technique, genetic algorithm, is applied to maximize the glide ratio while reducing the difference from the desired design parameters. …”
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1609
Rolling Bearing Fault Diagnosis Based on Optimized VMD and SSAE
Published 2024-01-01“…Firstly, the DBO algorithm is enhanced to improve its optimization precision and global optimization capability. …”
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1610
Beyond boundaries: AI-optimized global landslide susceptibility mapping
Published 2025-12-01“…This study addresses these gaps by developing an optimized framework using support vector regression (SVR) enhanced with meta-heuristic algorithms (grey wolf optimizer [GWO] and bat algorithm) to refine model hyper-parameters. …”
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1611
Research on LSTM-PPO Obstacle Avoidance Algorithm and Training Environment for Unmanned Surface Vehicles
Published 2025-02-01“…In response to the above problems, this paper proposes a long and short memory network-proximal strategy optimization (LSTM-PPO) intelligent obstacle avoidance algorithm for non-particle models in non-ideal environments, and designs a corresponding deep reinforcement learning training environment. …”
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1612
Optimizing Hyperparameters in Meta-Learning for Enhanced Image Classification
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1613
Optimization of a Coupled Neuron Model Based on Deep Reinforcement Learning and Application of the Model in Bearing Fault Diagnosis
Published 2025-06-01“…By comparing the coupled neuron model optimized with a reinforcement learning algorithm, particle swarm algorithm, and quantum particle swarm algorithm, the experimental results show that the coupled neuron model optimized with a deep reinforcement learning algorithm has the optimal signal-to-noise ratio of the output signal and recognition rate of the bearing faults, which are −13.0407 dB and 100%, respectively. …”
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1614
Leveraging prior mean models for faster Bayesian optimization of particle accelerators
Published 2025-04-01“…Abstract Tuning particle accelerators is a challenging and time-consuming task that can be automated and carried out efficiently using suitable optimization algorithms, such as model-based Bayesian optimization techniques. …”
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1615
Research on cutting mechanism and process optimization method of gear skiving
Published 2025-02-01“…Furthermore, a prediction model of cutting force and cutting temperature is established using a neural network optimized by genetic algorithm. …”
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1616
Numerical modeling and neural network optimization for advanced solar panel efficiency
Published 2025-07-01“…Conventionally, such optimization techniques—MPPT (Maximum Power Point Tracking) along with heuristic algorithms—suffer significantly from slow adaptability and track sub optimality under dynamic environments. …”
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1617
Modeling, optimization, and thermal management strategies of hydrogen fuel cell systems
Published 2025-09-01“…Optimization algorithms such as PSO, WOA, MIGA, and NSGA-II have shown promising results, including up to 15 % reduction in hydrogen consumption and 20 to 30 % improvement in thermal uniformity. …”
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1618
Research on the method of weight calculation and equipment arrangement optimization of tramcar
Published 2022-01-01“…Based on Isight optimization platform, multi-objective optimization algorithm was adopted to improve the equipment layout. …”
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1619
Synergistic integration of refined pelican optimization algorithm and deep neural networks for autonomous vehicle control in edge computing architectures
Published 2025-06-01“…The chief contributions of the present study have been threefold: (1) the improvement of a particular autonomous driving method optimized for mobile edge computing platforms; (2) the arrangement of an optimized MobileNet method employing the RPO algorithm that uses LiDAR sensor data for effective object recognition and path design; and (3) the construction of an indoor vehicle prototype by mean of a microcontroller and LiDAR sensors, after a comprehensive performance evaluation of inference models, and analyzing the trade-offs between input size and computational effectiveness. …”
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