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3341
Flex-route demand response transit scheduling based on station optimization
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3342
Development of scientific and methodological approaches to improve the efficiency of quarry transport operation
Published 2020-12-01“…It is concluded that it is necessary to develop scientific and methodological approaches to improve the operation of open pit transport. An algorithm for the operation of open pit transport in a simulation model has been developed, which allows taking into account the influence of the control and distribution system of dump trucks on the number of excavators and the timely delivery of dump trucks to storage points. …”
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3343
Performance enhancement of drone LiB state of charge using extended Kalman filter algorithm
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3344
Research review on improving the efficiency of multimodal transportation based on technological solutions
Published 2020-09-01“…Improving efficiency of multimodal transportation today is possible due to the optimization of the interaction system between the used modes of transport and transportation of goods. …”
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3345
Multi-Objective Optimization for Green BTS Site Selection in Telecommunication Networks Using NSGA-II and MOPSO
Published 2025-01-01“…Furthermore, a metaheuristic algorithm was employed to analyze the NP-Hardness of the model. …”
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3348
Location privacy protection method based on lightweight K-anonymity incremental nearest neighbor algorithm
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3349
Fusion of multi-scale and context for small target detection algorithm of unmanned aerial vehicle rescue
Published 2024-09-01“…Finally, balance L1 loss was used to optimize the loss function of the baseline algorithm and enhance the stability of the model during the process of detection. …”
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3350
Software-defined networking QoS optimization based on deep reinforcement learning
Published 2019-12-01“…To solve the problem that the QoS optimization schemes which based on heuristic algorithm degraded often due to the mismatch between parameters and network characteristics in software-defined networking scenarios,a software-defined networking QoS optimization algorithm based on deep reinforcement learning was proposed.Firstly,the network resources and state information were integrated into the network model,and then the flow perception capability was improved by the long short-term memory,and finally the dynamic flow scheduling strategy,which satisfied the specific QoS objectives,were generated in combination with deep reinforcement learning.The experimental results show that,compared with the existing algorithms,the proposed algorithm not only ensures the end-to-end delay and packet loss rate,but also improves the network load balancing by 22.7% and increases the throughput by 8.2%.…”
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3351
Study on the fusion of improved YOLOv8 and depth camera for bunch tomato stem picking point recognition and localization
Published 2024-11-01“…Initially, the Fasternet bottleneck in YOLOv8 is replaced with the c2f bottleneck, and the MLCA attention mechanism is added after the backbone network to construct the FastMLCA-YOLOv8 model for fruit stalk recognition. Subsequently, the optimized K-means algorithm, utilizing K-means++ for clustering centre initialization and determining the optimal number of clusters via Silhouette coefficients, is employed to segment the fruit stalk region. …”
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3352
An investigation on energy-saving scheduling algorithm of wireless monitoring sensors in oil and gas pipeline networks
Published 2024-10-01“…Our algorithms improve the energy efficiency and stability of the monitoring system and provide important technical support for future intelligent pipeline monitoring systems. …”
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3353
Data-Driven Cooperative Localization Algorithm for Deep-Sea Landing Vehicles Under Track Slippage
Published 2025-02-01“…In this study, a data-driven cooperative localization algorithm with a velocity prediction model is proposed to improve the positioning accuracy of DSLV under track slippage. …”
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3354
MSFA-YOLO: A Multi-Scale SAR Ship Detection Algorithm Based on Fused Attention
Published 2024-01-01“…In addition, the DenseASPP module is incorporated to enhance the model’s adaptability to ships of varying scales, improving its ca-pability to accommodate larger ships within lower model scales. …”
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3355
A Novel Two-Stage Learning-Based Phase Unwrapping Algorithm via Multimodel Fusion
Published 2025-01-01“…The major advantages of TLPU are as follows: 1) A high-resolution U-Net (HRU-Net) model trained on a dataset constructed according to InSAR interferometric geometry is utilized for the PhU for the first time, which effectively improves the performance of the DLPU. 2) TLPU utilizes the traditional PhU method to optimize the results of DLPU, addressing the issue of weak generalization ability of a single DLPU, while improving accuracy in areas with large-gradient changes. …”
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3356
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3357
Combination of dynamic TOPMODEL and machine learning techniques to improve runoff prediction
Published 2025-03-01“…The present study aims to evaluate the optimal combination of these parameters within the dynamic TOPMODEL framework using machine learning techniques to improve the accuracy of runoff predictions and bolster the model's reliability. …”
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3358
Comprehensive Comparison and Validation of Forest Disturbance Monitoring Algorithms Based on Landsat Time Series in China
Published 2025-02-01“…These findings highlight the necessity of region-specific calibration and parameter optimization tailored to specific disturbance types to improve forest disturbance monitoring accuracy, and also provide a solid foundation for future studies on algorithm modifications and ensembles.…”
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3359
Autonomous Greenhouse Cultivation of Dwarf Tomato: Performance Evaluation of Intelligent Algorithms for Multiple-Sensor Feedback
Published 2025-07-01“…For an optimal strategy, however, it is essential that control algorithms properly account for crop responses, which requires appropriate sensors, reliable data, and accurate models. …”
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Dual-objective optimization of prefabricated component logistics based on JIT strategy
Published 2024-12-01“…Its objectives are to reduce carbon emissions during logistics and enhance customer satisfaction. An improved Non-dominated Sorting Genetic Algorithm II (NSGA-II) is used to solve the model, offering enhanced solution diversity and local search capabilities. …”
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