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3841
A joint optimization method of multi backhaul link selection and power allocation in 6G
Published 2023-06-01“…Aiming at the problem of limited single backhaul link capability of base stations in hotspot areas of the 6G system, a joint optimization method was proposed for multi-backhaul link selection and power allocation in an elastic coverage system, so that the data packets can select the appropriate backhaul link and transmission power according to their service characteristics and link conditions.Firstly, the transmission delay of data packets on the small cell sub-queue was analyzed by using queuing theory.Then, the optimization objective was modeled with the maximum delay tolerance elasticity value.Finally, the optimization problem were solved by the Hungarian algorithm and the Lagrangian duality and gradient descent method.The simulation results show that, compared with the traditional algorithm, the algorithm proposed reduces the average delay of URLLC (ultra-reliable and low-latency communication) service data packets and eMBB (enhanced mobile broadband) service data packets by 17% and 14% respectively, and effectively improves the network transmission rate.…”
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3842
Kinematics Analysis and Performance Optimization of Low Coupling PRPaR/2CRR Parallel Mechanism
Published 2024-10-01“…What's more, a multi-objective optimization design model was established based on the comprehensive performance of the workspace volume, the global dexterity, and the global operability, and the optimal structural parameter size solution was calculated using the NSGA-Ⅱ algorithm. …”
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3843
UV-Vis spectroscopy coupled with firefly algorithm-enhanced artificial neural networks for the determination of propranolol, rosuvastatin, and valsartan in ternary mixtures
Published 2025-03-01“…An experimental design of 25 samples was employed as a calibration set, and a central composite design of 20 samples was used as a validation set. The firefly algorithm (FA) was evaluated as a variable selection procedure to optimize the developed ANN models resulting in simpler models with improved predictive performance as evident by lower relative root mean square error of prediction (RRMSEP) values compared to the full spectrum ANN models. …”
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3844
Control and Stability Analysis of Double Time-Delay Active Suspension Based on Particle Swarm Optimization
Published 2020-01-01“…Aiming at the application of time-delay feedback control in vehicle active suspension systems, this paper has researched the dynamic behavior of semivehicle four-degree-of-freedom structure including an active suspension with double time-delay feedback control, focusing on analyzing the vibration response and stability of the main vibration system of the structure. The optimal objective function is established according to the amplitude-frequency characteristics of the system, and the optimal time-delay control parameters are obtained by using the particle swarm optimization algorithm. …”
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3845
Energy Interaction and Energy Storage Sharing Optimization Method for Users, Base Stations, and Charging Stations
Published 2025-07-01“…Next, incorporating 0-1 integer variables, a solution method utilizes the adaptive differential evolution algorithm combined with the mixed-integer optimization theory. …”
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3846
Flexibility Resource Planning and Stability Optimization Methods for Power Systems with High Penetration of Renewable Energy
Published 2025-08-01“…Furthermore, to mitigate the uncertainty and fault risks associated with extreme weather events, a CVaR-based risk quantification framework is incorporated into a bi-level optimization model, effectively balancing investment costs and operational risks under uncertainty. …”
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3847
Multi-Objective Parameter Optimization of Electro-Hydraulic Energy-Regenerative Suspension Systems for Urban Buses
Published 2025-06-01“…To streamline multi-objective optimization processes, a particle swarm optimization–back propagation (PSO-BP) neural network surrogate model was developed to approximate the complex co-simulation system. …”
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3848
Numerical Simulation and Optimization of Wind Effects of Porous Parapets on Low-Rise Buildings with Flat Roofs
Published 2019-01-01“…This paper presents a procedure to optimize the porosity of parapets to improve the aerodynamic behavior of low-rise buildings with flat roofs, by coupling an optimization algorithm and computational fluid dynamics (CFD) simulations. …”
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3849
Inter-Satellite Handover Method Based Multi-Objective Optimization in Satellite-Terrestrial Integrated Network
Published 2023-09-01“…The high-speed motion of low-earth orbit communication satellites results in a highly dynamic network topology, and the spatio-temporal distribution of resources in the satellite-terrestrial integrated network is non-uniform.When multiple users and services switch between satellites, a large number of handover requests are triggered, leading to intensified network resource competition.As a result, the limited satellite resources cannot meet all the handover requests, leading to a significant decrease in handover success rate.In view of the above problem, the multi-objective optimization based satellite handover method was proposed.It introduced the satellite coverage spatio-temporal graph and transforms the dynamic continuous topology into static discrete snapshots, accurately depicted the connections between satellite nodes and users at different times and locations.The multi-objective optimization model was established for satellite handover decisions, and anadaptive accelerated multi-objective evolutionary algorithm(AAMOEA) was proposed to optimized user data rate and network load simultaneously, ensured handover success rate and enhanced network service capability.It built a STIN communication simulation environment and tested the multi user handover performance in a multi satellite overlapping coverage scenario.The results demonstrated that the multi-objective optimization-based satellite handover method achieved an average handover success rate improvement of over 20% compared to benchmark algorithms.…”
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3850
An Optimal Charging Strategy for PV-Based Battery Swapping Stations in a DC Distribution System
Published 2017-01-01“…Then, a particle swarm optimization (PSO) algorithm is developed to calculate the optimal charging power and to minimize the charging cost for each time slot. …”
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3851
Study on the peak shaving operation of cascade hydropower stations based on the plant-wide optimal curve
Published 2025-09-01“…This study proposes a novel method to enhance RES and hydropower utilization through: 1) Establishing a plant-wide optimal output-water level-outflow relationship curve based on the output-head-flow relationship and the flow-head loss and outflow-tailwater level relationship curves for each unit; 2) Developing a short-term peak shaving model for cascaded hydropower stations that incorporates wind and PV power which defines minimum coefficient of variation of residual load as objective functions, and improving discrete differential dynamic programming successive approximation (DDDPSA) method to solve it; 3) Analyzing the peak shaving capacity of the cascade hydropower station by varying water consumption for power generation. …”
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3852
Optimization of Urban Rail Transit Train Stock Utilization under Re-coupling Operation Mode
Published 2025-01-01“…The MTSP ( multiple traveling salesman problem) is introduced to construct an optimized train stock utilization model during the transition period from peak to off-peak passenger flow in urban rail transit. …”
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3853
Synergistic hyperspectral and SAR imagery retrieval of mangrove leaf area index using adaptive ensemble learning and deep learning algorithms
Published 2025-08-01“…We confirmed that 1D-CNN + DNNR provided an effective approach to estimating the mangrove LAI, as it produced a higher-accuracy inversion (R2 = 0.8685) than that of the AELR model. It was found in this study that the 1D-CNN improved the retrieval accuracy (R2) of the mangrove LAI from 0.097 to 0.1297 when compared with the traditional data dimension reduction (DDR) method, which demonstrated that the 1D-CNN was able to improve the inversion accuracy of the mangrove LAI. …”
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3854
Robust Sliding Mode Control Based on GA Optimization and CMAC Compensation for Lower Limb Exoskeleton
Published 2016-01-01“…A genetic algorithm (GA) is utilized to determine the optimal sliding surface and the sliding control law to improve performance of SMC. …”
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3855
Optimized dual NURBS curve interpolation for high-accuracy five-axis CNC path planning
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3856
Adaptive RFID Data Scheduling Using Proximal Policy Optimization for Reducing Data Processing Latency
Published 2025-01-01“…This paper presents a novel approach for dynamically offloading data using deep reinforcement learning, specifically employing the Proximal Policy Optimization (PPO) algorithm. The proposed method utilizes a central controller equipped with the PPO model to make intelligent, real-time reader selection decisions based on environmental factors such as reader load, tag mobility, and network conditions. …”
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3857
Optimal Scheduling of Biomass-Hybrid Microgrids with Energy Storage: An LSTM-PMOEVO Framework for Uncertain Environments
Published 2025-03-01“…Finally, a public dataset was utilized for the experiments to verify the performance of the proposed algorithm. Comparisons and discussions show that the proposed optimization strategies significantly improve the performance of PMOEVO, demonstrating marked advantages over six classical algorithms. …”
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3858
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3859
Electromagnetic Analysis and Multi-Objective Design Optimization of a WFSM with Hybrid GOES-NOES Core
Published 2025-07-01“…The optimized WFSM achieved a 13.97% increase in power density and a 1.0% improvement in efficiency compared to the baseline NOES model. …”
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3860
Incorporating soil moisture data into a machine learning framework improved the predictive accuracy of corn yields in the U.S.
Published 2025-10-01“…Leveraging machine learning (ML) techniques capable of handling large-scale datasets offers a promising alternative for uncovering hidden patterns and generating actionable insights to improve crop yield. We hypothesize that incorporating soil moisture and temperature data from land surface models into a ML framework will enhance accuracy of corn yield predictions. …”
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