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Showing 1,041 - 1,060 results of 2,583 for search '((\ source detection functions\ ) OR (( resources OR resources) selection function\ ))', query time: 0.28s Refine Results
  1. 1041

    Numerical prognosis of the dynamic response of the steel rectangular slab under the explosive load by Sławomir Onopiuk, Adam Stolarski, Ryszard Rekucki

    Published 2025-06-01
    “…Conclusions were also formulated regarding the requirements for the selection of parameters of the sensors recording both the function of real explosion pressure in time and the function of acceleration in time of the slab model during experimental tests.…”
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  2. 1042
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    Power Communication Network Recovery from Large-Scale Failures Based on Reinforcement Learning by Huibin JIA, Yonghe GAI, Baogang LI, Hongda ZHENG

    Published 2020-06-01
    “…Regarding this model, a heuristic algorithm based on reinforcement learning is proposed, in which the link recovery resources and the degree of importance of the damaged link in the failed service are taken into account to set the reward and penalty functions as well as the selection rules. …”
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  6. 1046
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    Water quality anomaly detection research based on GRU-PINN model by Zhao Xinyu

    Published 2025-01-01
    “…Maintaining high-quality water resources is essential for sustainable urban water resource management and public health. …”
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  9. 1049

    Current approaches to assessment of the impact of the environmental contamination on cancer risk by L. G. Solenova

    Published 2020-03-01
    “…Assessment of the impact of environmental contamination on cancer risk includes: •setting research priorities on the local, regional, and on the all-Russian levels; •the selection of the research that may be maximally socially profitable; •the choice of the research method that the most adequately meets the research objectives; •systemic analysis of the planed research to determine the availability of the resources, personnel, and information; •monitoring of atmospheric pollutions with analysis of the fraction composition of the particulate matters; •coordination of available data basis on environment and the population health conditions; •the implementation of the of molecular biology to determine prenosological manifestation of carcinogenesis and development of fine and diverse research methods on relationships between the environment and cancer risk.For effective implementation of the research objectives aimed to decrease the impact of hazard factors with special reference on cancer risk in the Russian population, it is necessary: to create training personnel capable of providing epidemiologic studies, using up-to day methods, publication of methodological materials, text books, and sufficient funding of studies.…”
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    Application of Machine Learning in Construction Productivity at Activity Level: A Critical Review by Ying Terk Lim, Wen Yi, Huiwen Wang

    Published 2024-11-01
    “…The review further found that the selection of ML models relies on each particular application, available data, and computational resources. …”
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  16. 1056

    Secondary Frequency Control of Islanded Microgrid Based on Deep Reinforcement Learning by Li WANG, Yuxiang JIANG, Xiangjun ZENG, Bin ZHAO, Junhao LI

    Published 2025-05-01
    “…The reward function balances the goals of frequency recovery and power allocation among distributed energy resources , ensuring consistency in action selection among the intelligent agents. …”
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  17. 1057

    Heat treatment control technology of high-strength steel gears based on support vector machine by Yanzhong Wang, Libin Zhang, Yulu Su, Hai Liu, HaiLong Yang, Yanyan Chen

    Published 2025-03-01
    “…At the present stage, the method of multi-parameter multi-level combination test block trial production is often used, but its production cycle is long, and the waste of human and material resources is serious. In this study, with the help of machine learning, a support vector machine prediction model of gear tissue distribution is constructed based on heat treatment parameters, and the radial basis functions kernel function is selected as the kernel function of the support vector machine to improve the accuracy of model prediction by optimizing the kernel parameters. …”
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