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721
Algorithms and probabilistic models of parameters of operation of in-plant power supply
Published 2021-05-01“…To investigate the operability of low-voltage shop networks of radial, trunk and mixed structure in optimal operating conditions of the equipment when modeling the impact of external factors, such as the root-mean-square load factor of the equipment, the temperature of the shop room and the calculated time interval on the operating parameters of the system. …”
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722
Charging pile fault prediction method combining whale optimization algorithm and long short-term memory network
Published 2025-05-01“…By introducing the whale optimization mechanism to globally optimize the key parameters of the neural network, the method improved the model’s ability to model complex time series data. …”
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723
DynaFusion-SLAM: Multi-Sensor Fusion and Dynamic Optimization of Autonomous Navigation Algorithms for Pasture-Pushing Robot
Published 2025-05-01“…The results indicate that when the RTAB-Map algorithm fuses with the multi-source odometry, its performance is significantly improved in the laboratory-simulated ranch scenario, the maximum absolute value of the error of the map measurement size is narrowed from 24.908 cm to 4.456 cm, the maximum absolute value of the relative error is reduced from 6.227% to 2.025%, and the absolute value of the error at each location is significantly reduced. …”
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724
Optimizing airway network efficiency with the A-star algorithm: a case study of Ho Chi Minh FIR
Published 2025-06-01“…To address these challenges, this study proposes optimizing the airway network in 2D space using the A-star algorithm, tailored for the HCM FIR. …”
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725
Bio-Inspired Multiobjective Optimization for Designing Content Distribution Networks
Published 2025-04-01Get full text
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726
Decision-making method for residual support force of hydraulic supports during pressurized moving under fragmented roof conditions in ultra-thin coal seams
Published 2025-03-01“…To address this challenge, this study proposed a novel decision-making method based on a Deep Hybrid Kernel Extreme Learning Machine (DHKELM) optimized by an Improved Dung Beetle Optimization (IDBO) algorithm. …”
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727
Optimizing SVC placement for enhanced voltage stability using a novel index and hybrid ABC-PSO algorithm
Published 2025-06-01“…The ABC-PSO hybrid algorithm converges very quickly to optimal solutions in 10 to 40 iterations and outperforms five state-of-the-art optimizers with a 100 % success rate for the IEEE 14-bus system and a mean computation time of 0.041 s per iteration. …”
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728
Optimal Design Method of a Hybrid CSP-PV Plant Based on Genetic Algorithm Considering the Operation Strategy
Published 2018-01-01“…In this paper, the operation strategy of the CSP-PV system is proposed for parabolic trough CSP system and PV system which are now commercially operated. Genetic algorithm is used to optimize the design of the system and calculate PV-installed capacity, battery capacity, and storage capacity of CSP system, making the system to achieve the lowest cost of electricity generation. …”
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729
Web services composition algorithm based on the location of backup service and probabilistic QoS model
Published 2016-10-01“…For the service selection problem, an improved multiple objective optimization(MOO)algorithm was adopted to calculate the feasible solution set using clustering and QoS model. …”
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730
Web services composition algorithm based on the location of backup service and probabilistic QoS model
Published 2016-10-01“…For the service selection problem, an improved multiple objective optimization(MOO)algorithm was adopted to calculate the feasible solution set using clustering and QoS model. …”
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731
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732
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733
An optimized method for short-term load forecasting based on feature fusion and ConvLSTM-3D neural network
Published 2025-01-01“…As renewable energy continues to penetrate modern power systems, accurate short-term load forecasting is crucial for optimizing power generation resource allocation and reducing operational costs. …”
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734
Diagnosing schizophrenia with routine blood tests: a comparative analysis of machine learning algorithms
Published 2025-08-01Get full text
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735
Recent advancements in stereolithography (SLA) and their optimization of process parameters for sustainable manufacturing
Published 2024-12-01“…Furthermore, the paper discusses the application of optimization methods like Genetic Algorithms and Artificial Neural Networks (ANN) to analyze, refine, and determine the optimal processing parameters for stereolithography. …”
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736
Advancing smart aquaculture: Cost-efficient strategies for climbing perch cultivation using AI-based models
Published 2025-12-01“…This study introduces a hybrid AI-based optimization framework to enhance climbing perch aquaculture in smart farming systems, targeting improvements in both productivity and cost-efficiency. …”
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737
Optimizing Multi-Echelon Delivery Routes for Perishable Goods with Time Constraints
Published 2024-12-01“…The results demonstrate that the initial solutions obtained through the k-medoids clustering algorithm based on spatio-temporal distance improved the overall cost optimization by 1.85% and 4.74% compared to the other two algorithms. …”
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738
Optimizing Human-Centric Warehouse Operations: A Digital Twin Approach Using Dynamic Algorithms and AI/ML
Published 2025-02-01Get full text
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739
Optimizing Container Repositioning Using a Sequential Insertion Algorithm for Pickup-Delivery Routing in Export-Import Operations
Published 2025-04-01“…This research contributes a practical approach with the potential to lower operational costs and mitigate congestion by improving fleet utilization. …”
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740
Multi-UAV Trajectory Optimization Under Dynamic Threats: An Enhanced GWO Algorithm Integrating a Priori and Real-Time Data
Published 2025-06-01“…Our research integrates a priori knowledge of threat zone locations, speeds, and directions with real-time data on the UAVs position relative to the threat zones to effectively manage dynamic threat zones, allowing UAVs to dynamically decide whether to navigate around or through these zones, thus significantly reducing trajectory costs. To further improve search efficiency and solution quality, strategies such as greedy initialization and K-means clustering are incorporated, enhancing the algorithms multi-objective optimization capabilities. …”
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