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2361
Precise GNSS Positioning with Time-differenced Carrier Phases at Variable Sampling Rates
Published 2025-07-01“…Most Global Navigation Satellite System (GNSS) receivers typically have a sampling rate at 1Hz. …”
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2362
ARIMA-Based Forecasting of Wastewater Flow Across Short to Long Time Horizons
Published 2025-06-01“…Improving urban wastewater treatment efficiency and quality is urgent for most cities. …”
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2363
Hyperspectral Imaging for Non-Destructive Moisture Prediction in Oat Seeds
Published 2025-06-01“…Subsequently, a dual-optimized neural network model, termed Bayes-ASFSSA-BP, was developed by incorporating Bayesian optimization and the Adaptive Spiral Flight Sparrow Search Algorithm (ASFSSA). …”
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2364
Reinforcement Learning for Computational Guidance of Launch Vehicle Upper Stage
Published 2022-01-01“…This manuscript investigates the use of a reinforcement learning method for the guidance of launch vehicles and a computational guidance algorithm based on a deep neural network (DNN). Computational guidance algorithms can deal with emergencies during flight and improve the success rate of missions, and most of the current computational guidance algorithms are based on optimal control, whose calculation efficiency cannot be guaranteed. …”
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2365
Real-Time Height Measurement for Moving Pedestrians
Published 2020-01-01“…Firstly, a normalization equation is presented to convert the depth image into the grey image for a lower time cost and better performance. Secondly, a difference-particle swarm optimization (D-PSO) algorithm is proposed to remove the complex background and reduce the noises. …”
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2366
Process-based modeling framework for sustainable irrigation management at the regional scale: integrating rice production, water use, and greenhouse gas emissions
Published 2025-06-01“…Here, we propose an advancing framework that addresses these problems by integrating a process-based soil–crop model with vital physiological effects, a novel method for model upscaling, and the non-dominated sorting genetic algorithm II (NSGA-II) multi-objective optimization algorithm at a parallel computing platform. …”
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2367
A lightweight lattice-based group signcryption authentication scheme for Internet of things
Published 2024-04-01“…In the key generation stage, the improved trapdoor diagonal matrix was designed to optimize the original image sampling algorithm required for key generation and reduce the overall time required for generating a large number of keys. …”
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2368
Optimum Design Research on the Link Mechanism of the JP72 Lifting Jet Fire Truck Boom System
Published 2024-12-01“…The fmincon function was used to realize the sequential quadratic programming (SQP) algorithm, which is one of the most effective methods to solve the constrained nonlinear optimization problems, for the optimal design. …”
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2369
Real-time temperature prediction of large-scale lithium battery module driven by data based on few measurement points
Published 2025-05-01“…Proper thermal management ensures uniform heat distribution, which is essential for optimizing efficiency, safety, and reliability. However, obtaining comprehensive real-time temperature data for large-scale battery systems is challenging due to the high costs, complexity, and impracticality of deploying extensive sensor networks. …”
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2370
Low power IoT device communication through hybrid AES-RSA encryption in MRA mode
Published 2025-04-01“…This modification optimizes computational efficiency and strengthens security.Furthermore, we investigate the feasibility of integrating the RSA and AES algorithms and propose a novel RSA-AES hybrid algorithm MRA. …”
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2371
A lightweight lattice-based group signcryption authentication scheme for Internet of things
Published 2024-04-01“…In the key generation stage, the improved trapdoor diagonal matrix was designed to optimize the original image sampling algorithm required for key generation and reduce the overall time required for generating a large number of keys. …”
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2372
Outdoor location scheme with fingerprinting based on machine learning of mobile cellular network
Published 2021-08-01“…The positioning scheme based on mobile cellular network technology is one of the important technical approaches to provide network optimization, emergency rescue, police patrol and location services.The traditional positioning scheme based on cell base station location information has low positioning accuracy and large positioning error, so it cannot meet the requirements of some positioning applications.The scheme based on fingerprint location can greatly improve the location accuracy, save computational cost and enhance the usability based on the coarse location scheme of the cell and become the hotspot of the research.Rasterization and non-rasterization of outdoor fingerprint location scheme based on machine learning were studied and analyzed to meet the business requirements of outdoor fingerprint location.By means of parameter weighting, data fitting and other methods, large-scale fingerprint data were cleaned to improve the effectiveness of data sources.Through the realization of sub-modules such as demarcating research area, rasterizing, constructing fingerprint database, training model, correcting model, non-rasterizing, rough positioning coupling, matching parameter and training parameter, the operation efficiency and positioning accuracy of the algorithm were analyzed and optimized, and the key indexes affecting the algorithm performance were determined.Then, the performance of two fingerprint-based localization schemewas analyzed based on the simulation results.Finally, the typical scenarios of the fingerprint location scheme based on machine learning in practical application were presented.…”
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2373
Robust fuzzy dynamic integrated environmental-economic-social scheduling considering demand response and user’s satisfaction with electricity under multiple uncertainties
Published 2025-02-01“…Taking the lowest comprehensive operation cost as the economic objective, the smallest emissions of CO2 and atmospheric pollutants as environmental objective and the largest user’s comprehensive satisfaction with electricity as the social objective, based on the robust fuzzy theory, the multi-objective uncertainty optimal scheduling model is constructed, which is transformed into deterministic model and then solved by intelligent optimization algorithm. …”
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2374
A Full-Profile Measurement Method for an Inner Wall with Narrow-Aperture and Large-Cavity Parts Based on Line-Structured Light Rotary Scanning
Published 2025-04-01“…Considering the structural constraints in the measurement of narrow-aperture and large-cavity parts, a structural optimization algorithm is designed to enable the sensor to achieve a high theoretical measurement resolution while satisfying the geometric constraints of the measured parts. …”
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2375
DGCLCMI: a deep graph collaboration learning method to predict circRNA-miRNA interactions
Published 2025-04-01“…Next, we present a joint model that combines an improved neural graph collaborative filtering method with a feature extraction network for optimization. …”
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2376
Comprehensive Evaluation and Trade‐Off of Top‐Level Requirements for BWB UAVs
Published 2025-07-01“…A parallelizable subset‐simulation optimization algorithm is implemented to iteratively refine the design, thereby maximizing overall system competitiveness. …”
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2377
Anti-disturbance predictive control for path tracking of unmanned agricultural vehicles based on safety distance
Published 2025-03-01“…Subsequently, an automatic optimization algorithm for the reference point of the agricultural vehicle is designed to prevent excessive steering during path tracking. …”
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2378
Anti-disturbance predictive control for path tracking of unmanned agricultural vehicles based on safety distance
Published 2025-03-01“…Subsequently, an automatic optimization algorithm for the reference point of the agricultural vehicle is designed to prevent excessive steering during path tracking. …”
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2379
Heuristic Binary Search for Modulated Predictive Control
Published 2025-01-01“…Experimental results comparing three variants of the Predictive Torque Control (one vector, three vector and modulated) show improvements in torque and flux ripple and improvements of current THD up to 30% over classic Modulated Predictive Torque Control implementation with reduced or similar computational cost. …”
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2380
Prediction of COD Degradation in Fenton Oxidation Treatment of Kitchen Anaerobic Wastewater Based on IPSO-BP Neural Network
Published 2025-01-01“…The Fenton oxidation process is used to treat kitchen anaerobic wastewater, and the effects of H2O2 dosage, Fe2+ dosage, reaction time and pH value on chemical oxygen demand (COD) degradation efficiency are explored. The improved particle swarm optimization (IPSO) algorithm is used to optimize the back propagation (BP) neural network, and a prediction model of COD degradation is established based on IPSO-BP neural network. …”
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