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  1. 1101

    Parametric-modeling-based multi-objective thermoelastic optimization of rudder structures by Shi Guanghui, Bao Yuhao, Wu Wenhua, Guo Guiqiang, Lin Ye, Zhang Xiaopeng, Tao Ran

    Published 2025-01-01
    “…These optimization problems are solved using a compromise programming algorithm. …”
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    Article
  2. 1102

    Grey Wolf Optimization- and Particle Swarm Optimization-Based PD/I Controllers and DC/DC Buck Converters Designed for PEM Fuel Cell-Powered Quadrotor by Habibe Gursoy Demir

    Published 2025-04-01
    “…Both optimizers work together in the system and try to minimize tracking errors while also minimizing power consumption by using suitable objective functions. …”
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    Article
  3. 1103

    A review of state-of-the-art resolution improvement techniques in SPECT imaging by Zhibiao Cheng, Ping Chen, Jianhua Yan

    Published 2025-01-01
    “…It delves into advancements in detector design and modifications, projection sampling techniques, traditional reconstruction algorithm development and optimization, and the emerging role of deep learning. …”
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    Article
  4. 1104

    An energy-saving virtual machine scheduling algorithm for resource management based on cloud computing technology by Liangyu Zhang

    Published 2025-04-01
    “…Therefore, the algorithm proposed in this paper can effectively reduce energy consumption while avoiding frequent migration of virtual machines, and the innovation in genetic algorithm optimization strategy improves the overall efficiency and stability of scheduling.…”
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    Article
  5. 1105

    DECISION TREE WITH HILL CLIMBING ALGORITHM BASED SPECTRUM HOLE DETECTION IN COGNITIVE RADIO NETWORK by N Suganthi, R Meenakshi, A Sairam, M Parvathi

    Published 2025-06-01
    “…The objective of the DTHC method is to improve detection accuracy while minimizing false alarm rates. …”
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    Article
  6. 1106
  7. 1107

    Impact of surrogate model accuracy on performance and model management strategy in surrogate-assisted evolutionary algorithms by Yuki Hanawa, Tomohiro Harada, Yukiya Miura

    Published 2025-09-01
    “…Surrogate-assisted evolutionary algorithms (SAEAs) are widely used to solve expensive optimization problems where evaluating candidate solutions is computationally intensive. …”
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    Article
  8. 1108

    VRU-YOLO: A Small Object Detection Algorithm for Vulnerable Road Users in Complex Scenes by Yunxiang Liu, Yuqing Shi

    Published 2025-01-01
    “…Additionally, a lightweight Optimized Shared Detection Head (OSDH-Head) is introduced, reducing computational complexity while improving detection efficiency. …”
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    Article
  9. 1109

    Resource-Efficient Context-Aware Dynamical Decoupling Embedding for Arbitrary Large-Scale Quantum Algorithms by Paul Coote, Roman Dimov, Smarak Maity, Gavin S. Hartnett, Michael J. Biercuk, Yuval Baum

    Published 2025-02-01
    “…We introduce and implement GraphDD: an efficient method for real-time, circuit-specific, optimal embedding of dynamical decoupling (DD) into executable quantum algorithms. …”
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    Article
  10. 1110

    BED-YOLO: An Enhanced YOLOv10n-Based Tomato Leaf Disease Detection Algorithm by Qing Wang, Ning Yan, Yasen Qin, Xuedong Zhang, Xu Li

    Published 2025-05-01
    “…In this paper, we propose an improved tomato leaf disease detection method based on the YOLOv10n algorithm, named BED-YOLO. …”
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  11. 1111

    Resource allocation strategy based on optimal matching auction in the enterprise network by Xin CONG, Lingling ZI, Xueli SHEN

    Published 2019-08-01
    “…To address the issue that the owners of computer are selfish in the enterprise networks,which caused the low available number of resource nodes and low efficiency of resource allocation,an optimized matching resource allocation strategy OMRA was proposed and its core was the auction mechanism.Selfishness was restrained and the number of available resources was increased by OMRA,so as the operating efficiency of the whole auction market was improved.First,the initial prices were determined by normalizing the costs of different type of resources on the beginning of auction.Secondly,an optimal matching auction algorithm was designed to maximize the interests of the auction markets.Then,service perfecting algorithm was performed such that the sellers could get more services at the current transaction value,thus ensuring the benefits of resource providers.At last,a request price updating algorithm was adopted to assurance that both sellers and buyers could get priorities in the next auction processing.Compared with the cloud resource allocating algorithm via fitness-enabled auction (CRAA/FA),the experiment results indicate that the efficiency of resource allocation improves by 10% and the benefits of market increase by 11.4%.…”
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  12. 1112

    Research on prediction algorithm of effluent quality and development of integrated control system for waste-water treatment by JianWun Lai

    Published 2025-06-01
    “…The ICS is superior to standard WWTCS by a vital error boundary, minimizing energy consumption by 17% and boosting chemical-based consumption optimization by 24%. With an average removal rate of 94.23% for Chemical Oxygen Demand (COD) compared to 88.76% for standard systems, the findings from experiments exhibited significant performance improvements.…”
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  13. 1113

    Investigating the performance of random oversampling and genetic algorithm integration in meteorological drought forecasting with machine learning by Tahsin Baykal, Özlem Terzi, Gülsün Yıldırım, Emine Dilek Taylan

    Published 2025-05-01
    “…Therefore, this study aims to evaluate the effectiveness of machine learning methods for meteorological drought estimation and to integrate Random Oversampling (ROS) and Genetic Algorithm (GA) methods to improve estimation accuracy. …”
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    Article
  14. 1114

    Estimation of the Ultimate Bearing Capacity of the Rocks via Utilization of the AI-Based Frameworks by Bianca Damico, Matteo Conti

    Published 2024-12-01
    “…The approach adopted here is new and solves the problem using KNN combined with two modern nature-inspired optimization frameworks, namely the Honey Badger Algorithm (HBA) and Equilibrium Slime Mould Algorithm (ESMA). …”
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  15. 1115

    Heuristic Algorithms for the Heterogeneous Vehicle Routing Problem With Time Windows, Customers Priority, Pickup and Delivery by Moayad Tanash, Rami As'Ad

    Published 2025-01-01
    “…Both heuristics possess a two-phase structure, where the first phase yields highly prudent initial solutions employing a Greedy Randomized Adaptive Search Procedure (GRASP) in the first heuristic, and Priority-Based Ant Colony Optimization (PBACO) in the second heuristic. As for the second phase, both heuristics embrace a common Variable Neighborhood Search (VNS) algorithm that explores seven different neighborhoods to improve upon the initial solutions. …”
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  16. 1116

    Vehicular cache nodes selection algorithm under load constraint in C-V2X by Zhexin XU, Kaimeng GAO, Wenkang JIA, Yi WU

    Published 2021-03-01
    “…In order to solve the problem that the C-V2X vehicle topology in urban environment was highly dynamic and the load capacity of vehicle nodes was limited, and improve the utilization of vehicular cache resources and reduce the load of base station, a vehicle cache nodes selection algorithm under load constraints was proposed.Firstly, by defining the link stability metric, the predicted weight adjacency matrix was constructed to describe the vehicular micro-topology in essence.Next, the objective function was further constructed under the load constraints and non-overlapping coverage constraint, which maximized the average link weight of the clusters by using the least cache nodes.Finally, the greedy concept was then introduced and the node states were reasonably defined.As a result, the minimum dominating set of the vehicle topology was figured out under the load constraints.Besides, the serviced neighbor nodes were then determined preferentially.The simulation results show that the proposed algorithm is close to the global optimal results in terms of the number of cache nodes and the average weight of cluster links.Moreover, the repeated response ratio of the proposed algorithm is always zero while the request response ratio can achieve the theoretical upper bound.Furthermore, the response times of cache resources can be also effectively improved.…”
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  17. 1117

    Significance of Machine Learning-Driven Algorithms for Effective Discrimination of DDoS Traffic Within IoT Systems by Mohammed N. Alenezi

    Published 2025-06-01
    “…Findings revealed that the RF model outperformed other models by delivering optimal detection speed and remarkable performance across all evaluation metrics, while KNN (K = 7) emerged as the most efficient model in terms of training time.…”
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