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Showing 7,801 - 7,820 results of 8,275 for search '(( improved (cost OR most) optimization algorithm ) OR ( improved model optimization algorithm ))', query time: 0.42s Refine Results
  1. 7801

    A novel seismic inversion method based on multiple attributes and machine learning for hydrocarbon reservoir prediction in Bohai Bay Basin, Eastern China by Zongbin Liu, Jianmin Zhu, Bo Tian, Rui Zhang, Yongheng Fu, Yuan Liu, Lixin Wang

    Published 2024-12-01
    “…GA helps CNNs to get an optimal solution in a fast speed. The results reveal that the model's sand thickness predictions closely match the actual measurements at wells, with a new horizontal well's alignment with the predicted output reaching an accuracy of 85.1%. …”
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  2. 7802

    Design of and Experiment with a Dual-Arm Apple Harvesting Robot System by Wenlei Huang, Zhonghua Miao, Tao Wu, Zhengwei Guo, Wenkai Han, Tao Li

    Published 2024-11-01
    “…Finally, to improve collaboration efficiency, a multi-arm task planning method based on a genetic algorithm is used to optimize the target harvesting sequence for each arm. …”
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  3. 7803

    Swin‐YOLOX for autonomous and accurate drone visual landing by Rongbin Chen, Ying Xu, Mohamad Sabri bin Sinal, Dongsheng Zhong, Xinru Li, Bo Li, Yadong Guo, Qingjia Luo

    Published 2024-12-01
    “…And finally, the RBN data batch normalization method is used to improve the performance of the model in extracting effective features from the data. …”
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  4. 7804

    A Matheuristic Approach Based on Variable Neighborhood Search for the Static Repositioning Problem in Station-Based Bike-Sharing Systems by Julio Mario Daza-Escorcia, David Álvarez-Martínez

    Published 2024-11-01
    “…To solve this problem, we propose a <i>matheuristic</i> based on a <i>variable neighborhood search</i> combined with several improving algorithms, including an <i>integer linear programming model</i> to optimize loading instructions. …”
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  5. 7805

    Comparison of Machine Learning Methods for Predicting Electrical Energy Consumption by Retno Wahyusari, Sunardi Sunardi, Abdul Fadlil

    Published 2025-02-01
    “…Data pre-processing, specifically min-max normalization, is crucial for improving the accuracy of distance-based algorithms like KNN. …”
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  6. 7806

    Combining Process Mining and Process Simulation in Healthcare: A Literature Review by Evelyn Salas, Michael Arias, Santiago Aguirre, Eric Rojas

    Published 2024-01-01
    “…By reviewing distinct scholarly databases, 31 research studies were selected for analysis, from which it was possible to characterize case studies, techniques, tools, perspectives and algorithms, as well as to identify key limitations. …”
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  7. 7807

    A Secure Data Collection Method Based on Deep Reinforcement Learning and Lightweight Authentication by Yunlong Wang, Jie Zhang, Guangjie Han, Dugui Chen

    Published 2025-05-01
    “…To address such challenges, we propose a lightweight chain authentication protocol for scalable IoT environments (LCAP-SIoT), which uses Physical Unclonable Functions (PUFs) and distributed authentication to secure communications, and a secure data collection algorithm, named LS-QMIX, which fuses the LCAP-SIoT and Q-learning Mixer (QMIX) algorithm to optimize the path planning and cooperation efficiency of the multi-UAV system. …”
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  8. 7808

    Estimating Suitable Areas for Dry Almond (Amygdalus communis L.) Cultivation Development in Fars Province using Geographic Information System (GIS) by Ayatollah Karami, Alireza Salehi, Vida Aliyari

    Published 2025-12-01
    “…Almond cultivation not only has high nutritional value but can also contribute to ecosystem improvement, increase farmers' income, and create job opportunities. …”
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  9. 7809

    Neural network technologies for forecasting and controlling electricity consumption in energy systems by the genetic method by Nikolay K. Poluyanovich, Oleg V. Kachelaev, Marina N. Dubyago, Talia Hernandez Falcón

    Published 2025-03-01
    “…Based on the results of training and testing, the genetic algorithm confirmed the possibility of automating the selection of optimal hyperparameters and obtaining forecasts of greater accuracy and the possibility.…”
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  10. 7810

    2H-MoS2 lubrication-enhanced MWCNT nanocomposite for subtle bio-motion piezoresistive detection with deep learning integration by Ke-Yu Yao, Derek Ka-Hei Lai, Hyo-Jung Lim, Bryan Pak-Hei So, Andy Chi-Ho Chan, Patrick Yiu-Man Yip, Duo Wai-Chi Wong, Bingyang Dai, Xin Zhao, Siu Hong Dexter Wong, James Chung-Wai Cheung

    Published 2025-05-01
    “…Herein, we present an environmentally friendly, low-cost, and nonionic fabrication approach for a 2H-phase molybdenum disulfide (2H-MoS2)-enhanced multi-walled carbon nanotube (MWCNT) strain sensor, developed via a systematically optimized vacuum-assisted filtration process. …”
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  11. 7811

    A Composite Network for CS ISAR Integrating Deep Adaptive Sampling and Imaging by Lianzi Wang, Ling Wang, Miguel Heredia Conde, DaiYin Zhu

    Published 2025-01-01
    “…However, the existing CS ISAR imaging methods based on deep learning (DL) mainly focus on improving the performance of the reconstruction algorithm while ignoring the potential room for improvement given by the design of the measurement matrix. …”
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  12. 7812

    Can Stereoscopic Density Replace Planar Density for Forest Aboveground Biomass Estimation? A Case Study Using Airborne LiDAR and Landsat Data in Daxing’anling, China by Xuan Mu, Dan Zhao, Zhaoju Zheng, Cong Xu, Jinchen Wu, Ping Zhao, Xiaomin Li, Yong Pang, Yujin Zhao, Tianyu An, Yuan Zeng, Bingfang Wu

    Published 2025-03-01
    “…The results of 10-fold cross-validation demonstrated the superiority of the stereo method over the planar method, with RF outperforming SLR. The optimal RF-based stereo model of H<sub>AM</sub> (R<sup>2</sup> = 0.65, rRMSE = 26.05%) significantly improved AGB estimation compared to the planar model (R<sup>2</sup> = 0.59, rRMSE = 30.41%). …”
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  13. 7813

    Advanced Estimation of Winter Wheat Leaf’s Relative Chlorophyll Content Across Growth Stages Using Satellite-Derived Texture Indices in a Region with Various Sowing Dates by Jingyun Chen, Quan Yin, Jianjun Wang, Weilong Li, Zhi Ding, Pei Sun Loh, Guisheng Zhou, Zhongyang Huo

    Published 2025-07-01
    “…Following a two-step variable selection method, Random Forest (RF)-LassoCV, five machine learning algorithms were applied to develop estimation models. …”
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  14. 7814

    Detection Method for Safety Helmet Wearing on Construction Sites Based on UAV Images and YOLOv8 by Xin Jiao, Cheng Li, Xin Zhang, Jian Fan, Zhenwei Cai, Zhenglong Zhou, Ying Wang

    Published 2025-01-01
    “…To address these issues, this study proposes a helmet detection method based on unmanned aerial vehicles (UAVs) and the YOLOv8 object detection algorithm. The method utilizes UAVs to flexibly capture construction site images, combined with the optimized YOLOv8s model, and employs transfer learning to annotate and train labels for “person” and “helmet”. …”
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  15. 7815

    Analysis of Blockchain-Technology by Danylo Dvorchuk, Iryna Shpinareva

    Published 2025-06-01
    “…The research also highlights emerging trends in blockchain development, particularly hybrid models and AI-driven optimization techniques, which can enhance blockchain efficiency and security. …”
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  16. 7816

    Real-time mobile broadband quality of service prediction using AI-driven customer-centric approach by Ayokunle A. Akinlabi, Folasade M. Dahunsi, Jide J. Popoola, Lawrence B. Okegbemi

    Published 2025-06-01
    “…Three (3) classification algorithms including Random Forest (RF), Support Vector Machine (SVM) and Extreme Gradient Boosting (XGBoost) were trained using the QoS dataset and then evaluated in order to determine the most effective model based on certain evaluation metrics – accuracy, precision, F1-Score and recall. …”
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  17. 7817

    Application of artificial intelligence in the diagnosis of malignant digestive tract tumors: focusing on opportunities and challenges in endoscopy and pathology by Yinhu Gao, Peizhen Wen, Yuan Liu, Yahuang Sun, Hui Qian, Xin Zhang, Huan Peng, Yanli Gao, Cuiyu Li, Zhangyuan Gu, Huajin Zeng, Zhijun Hong, Weijun Wang, Ronglin Yan, Zunqi Hu, Hongbing Fu

    Published 2025-04-01
    “…Results In the field of endoscopy, multiple deep learning models have significantly improved detection rates in real-time polyp detection, early gastric cancer, and esophageal cancer screening, with some commercialized systems successfully entering clinical trials. …”
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  18. 7818

    Multi-Source, Fault-Tolerant, and Robust Navigation Method for Tightly Coupled GNSS/5G/IMU System by Zhongliang Deng, Zhichao Zhang, Zhenke Ding, Bingxun Liu

    Published 2025-02-01
    “…Compared with standard Kalman filtering (EKF) and advanced multi-rate Kalman filtering (MRAKF), the proposed algorithm achieved 28.3% and 53.1% improvements in its <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>1</mn><mi>σ</mi></mrow></semantics></math></inline-formula> error, respectively, significantly enhancing the accuracy and reliability of the multi-source fusion navigation system.…”
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  19. 7819

    Evaluating the performance and feasibility of integrating thermoelectric generators with solar photovoltaic panels: A case study by D Lakshmi Satya Nagasri, ram kumar Alajingi, Ponnambalam Pathipooranam, S. Senthil raja, Mohd Faiz bin Mohd Salleh, R. Marimuthu

    Published 2024-12-01
    “…Further, a conclusion is drawn from the techno-economic analysis to focus on optimizing the number of TEGs placed under SPV and improving MPPT algorithms to enhance performance and reduce costs.…”
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  20. 7820

    ES-Net Empowers Forest Disturbance Monitoring: Edge–Semantic Collaborative Network for Canopy Gap Mapping by Yutong Wang, Zhang Zhang, Jisheng Xia, Fei Zhao, Pinliang Dong

    Published 2025-07-01
    “…Canopy gaps are vital microhabitats for forest carbon cycling and species regeneration, whose accurate extraction is crucial for ecological modeling and smart forestry. However, traditional monitoring methods have notable limitations: ground-based measurements are inefficient; remote-sensing interpretation is susceptible to terrain and spectral interference; and traditional algorithms exhibit an insufficient feature representation capability. …”
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