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Showing 401 - 420 results of 881 for search '(( improved most optimization algorithm ) OR ( improve model optimization algorithm ))~', query time: 0.28s Refine Results
  1. 401
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    Estimating forest aboveground carbon sink based on landsat time series and its response to climate change by Kun Yang, Kai Luo, Jialong Zhang, Bo Qiu, Feiping Wang, Qinglin Xiao, Jun Cao, Yunrun He, Jian Yang

    Published 2025-01-01
    “…We found that (1) GA can effectively improve the estimation accuracy of RF, the R 2 can be improved by up to 34.8%, and the optimal GA-RF model R 2 is 0.83. (2) The CSI of Pinus densata in Shangri-La was 0.45–0.72 t C·hm− 2 from 1987 to 2017. (3) Precipitation has the most significant effect on CSI. …”
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  3. 403

    Reliability evaluation of dynamic face recognition systems based on improved Fuzzy Dynamic Bayesian Network by Zhiqiang Liu, Wenbo Zhu, Hongzhou Zhang, Shengjin Wang, Lu Fang, Weijun Hong, Hua Shao, Guopeng Wang

    Published 2020-03-01
    “…Subsequently, we infer to solve the fuzzy reliability state probabilities of the six systems with Netica and get two most important factors with the improved fuzzy C-means algorithm. …”
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    The Study of Roadside Visual Perception in Internet of Vehicles Based on Improved YOLOv5 and CombineSORT by LI Xiaohui, YANG Jie, XIA Qin

    Published 2025-01-01
    “…It indicates that most algorithms can achieve good detection results when the targets are sparse, and the lightweight models may have more advantages with considering the demand of computing resources. …”
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  7. 407
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    Predictive Ecological Cooperative Control of Electric Vehicles Platoon on Hilly Roads by Bingbing Li, Weichao Zhuang, Boli Chen, Hao Zhang, Sheng Yu, Jianrun Zhang, Guodong Yin

    Published 2025-03-01
    “…Unlike most existing literature that focuses on suboptimal coordination under predefined leading vehicle trajectories, this strategy employs an approach based on the combination of a long short-term memory network (LSTM) and genetic algorithm (GA) optimization (GA-LSTM) to predict the future speed of the leading vehicle. …”
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  9. 409

    Data-Driven Battery Remaining Life Prediction Based on ResNet with GA Optimization by Jixiang Zhou, Weijian Huang, Haiyan Dai, Chuang Wang, Yuhua Zhong

    Published 2025-05-01
    “…To this end, this paper proposes a data-driven lithium-ion battery life prediction method based on residual network (ResNet) and genetic algorithm (GA) optimization, which is designed to screen the features of the lithium-ion battery training data in order to effectively reduce the redundant features and improve the prediction performance of the model. …”
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  10. 410

    Multi objective optimization and experimental investigation of the stirring performance of a novel micro actuator by Zhuowei He, Junjie Lei, Jingjing Yang, Huba Zhu

    Published 2025-05-01
    “…Subsequently, the Non-dominated Sorting Genetic Algorithm III (NSGA-III) is utilized for Multi-Objective Optimization to identify the optimal combination of structural parameters. …”
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  11. 411

    Conditional distributionally robust dispatch for integrated transmission-distribution systems via distributed optimization by Jie Li, Xiuli Wang, Zhicheng Wang, Zhenzi Song

    Published 2025-05-01
    “…This paper closes this gap by proposing a conditional distributionally robust optimization (DRO) method for ITDSs. Specifically, a novel ambiguity set is built by exploiting the dependence of the wind power forecast error on its forecast value, which differs from most of the existing ones. …”
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  12. 412

    Bionic Compass Method Based on Atmospheric Polarization Optimization in Non-Ideal Clear Condition by Yuyang Li, Xia Wang, Min Zhang, Ruiqiang Li, Qiyang Sun

    Published 2024-11-01
    “…This paper proposes a bionic navigation method based on atmospheric polarization optimization to improve heading accuracy under non-ideal clear conditions. …”
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  13. 413
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  15. 415

    Optimizing Q-Learning for Automated Cavity Filter Tuning: Leveraging PCA and Neural Networks by Aghanim Amina, Otman Oulhaj, Oukaira Aziz, Lasri Rafik

    Published 2025-01-01
    “…To overcome these limitations, PCA is applied to minimize the dimensionality of the S11 response data, keeping only the most relevant information while improving computational efficiency. …”
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    Enhancing Port Energy Autonomy Through Hybrid Renewables and Optimized Energy Storage Management by Dimitrios Cholidis, Nikolaos Sifakis, Nikolaos Savvakis, George Tsinarakis, Avraam Kartalidis, George Arampatzis

    Published 2025-04-01
    “…By bridging the gap between theoretical modeling and practical implementation, it offers a scalable and adaptable solution for improving cost efficiency and energy resilience in port operations.…”
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  18. 418

    Meta-Features Extracted from Use of kNN Regressor to Improve Sugarcane Crop Yield Prediction by Luiz Antonio Falaguasta Barbosa, Ivan Rizzo Guilherme, Daniel Carlos Guimarães Pedronette, Bruno Tisseyre

    Published 2025-05-01
    “…However, enhancing prediction models by incorporating new features extracted through regressions executed on the original dataset features can potentially improve predictive outcomes. …”
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  19. 419

    Prediction of performance and emission features of diesel engine using alumina nanoparticles with neem oil biodiesel based on advanced ML algorithms by M. S. Aswathanrayan, N. Santhosh, Srikanth Holalu Venkataramana, Kurugundla Sunil Kumar, Sarfaraz Kamangar, Amir Ibrahim Ali Arabi, Sameer Algburi, Osamah J. Al-sareji, A. Bhowmik

    Published 2025-04-01
    “…Abstract The growing need for sustainable energy sources and stricter environmental regulations necessitate the development of alternative fuels with lower emissions and improved performance. This study addresses these challenges by optimizing the performance and emission characteristics of a single-cylinder diesel engine powered by neem oil biodiesel blends enhanced with alumina nanoparticlesusing the powerful desirability-based optimization. …”
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  20. 420

    Explainable Artificial Intelligence (XAI) for Flood Susceptibility Assessment in Seoul: Leveraging Evolutionary and Bayesian AutoML Optimization by Kounghoon Nam, Youngkyu Lee, Sungsu Lee, Sungyoon Kim, Shuai Zhang

    Published 2025-06-01
    “…Ten topographic and environmental conditioning factors were selected as model inputs. We first employed the Tree-based Pipeline Optimization Tool (TPOT), an evolutionary AutoML algorithm, to construct baseline ensemble models using Gradient Boosting (GB), Random Forest (RF), and XGBoost (XGB). …”
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