Showing 41 - 60 results of 4,920 for search '(( source optimization methods ) OR ( sources optimization methods ))', query time: 0.40s Refine Results
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    Data-driven and physics-constrained acoustic holography based on optimizer unrolling by Pagavino Manuel, Zotter Franz

    Published 2025-01-01
    “…The network retrieves the strengths of equivalent sources from measurements by unrolling an iterative optimizer, whose regularizing parameters are inferred via supervised learning. …”
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    Inversion of electric field component Ex in the SOTEM method based on the improved particle swarm optimization algorithm by Jifeng ZHANG, Changjian CHEN, Yuteng LI, Xiran YOU, Ziben MA

    Published 2025-04-01
    Subjects: “…grounded-source short-offset transient electromagnetic (sotem) method…”
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  5. 45

    Advances in Multi-Source Navigation Data Fusion Processing Methods by Xiaping Ma, Peimin Zhou, Xiaoxing He

    Published 2025-04-01
    “…Additionally, methods based on Factor Graph Optimization (FGO) have also demonstrated advantages in multi-source data fusion, offering better handling of global consistency problems. …”
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  6. 46

    ENERGETICALLY OPTIMAL WORK OF WATER INTAKE STRUCTURES FROM UNDERGROUND SOURCES by I. Yu. Purusova

    Published 2019-06-01
    “…Objectives Perfecting of the existing schemes of water delivery in the pure tank on a pressure piping and increase in efficiency of submersible pumps on water intaking constructions from underground sources. Discusses the negative manifestations in the operation of water intaking constructions from underground. …”
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    Optimized Configuration of Multi-Source Measurement Devices Based on Distributed Principles by Yuhao Xu, Jiaqi Zhang, Jing Zhao, Xiaoyu Zhang, Jinming Ge

    Published 2025-02-01
    “…Considering the difficult problem of optimizing the configuration of multi-source measurement devices due to the large number of nodes, a distributed optimal configuration framework for multi-source measurement data is proposed. …”
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    Convolutive blind source separation method based on tensor decomposition by Baoze MA, Tianqi ZHANG, Zeliang AN, Pan DENG

    Published 2021-08-01
    “…A convolutive blind source separation algorithm was proposed based on tensor decomposition framework, to address the estimation of mixed filter matrix and the permutation alignment of frequency bin simultaneously.Firstly, the tensor models at all frequency bins were constructed according to the estimated autocorrelation matrix of the observed signals.Secondly, the factor matrix corresponding to each frequency bin was calculated by tensor decomposition technique as the estimated mixed filter matrix for that bin.Finally, a global optimal permutation strategy with power ratio as the permutation alignment measure was adopted to eliminate the permutation ambiguity in all the frequency bins.Experimental results demonstrate that the proposed method achieves better separation performance than other existing algorithms when dealing with convolutive mixed speech under different simulation conditions.…”
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    Stochastic Optimization Scheduling Method for Mine Electricity–Heat Energy Systems Considering Power-to-Gas and Conditional Value-at-Risk by Chao Han, Yun Zhu, Xing Zhou, Xuejie Wang

    Published 2025-08-01
    “…To fully accommodate renewable and derivative energy sources in mine energy systems under supply and demand uncertainties, this paper proposes an optimized electricity–heat scheduling method for mining areas that incorporates Power-to-Gas (P2G) technology and Conditional Value-at-Risk (CVaR). …”
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  16. 56

    Optimizing context-based location extraction by tuning open-source LLMs with RAG by Zifu Wang, Yahya Masri, Anusha Srirenganathan Malarvizhi, Tayven Stover, Samir Ahmed, David Wong, Yongyao Jiang, Yun Li, Mathieu Bere, Daniel Rothbart, Dieter Pfoser, David Marshall, Chaowei Yang

    Published 2025-08-01
    “…Extracting the geographic locations from text within their contexts is challenging, even with Natural Language Processing (NLP) tools and the latest Large Language Models (LLMs). We propose to optimize LLMs using Retrieval-Augmented Generation (RAG) and prompt-tuning methods, such as zero-shot and instruction-based prompting to improve the precision of extracting location information from news. …”
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  17. 57

    Identifying the Combined Impacts of Sensor Quantity and Location Distribution on Source Inversion Optimization by Shushuai Mao, Jianlei Lang, Feng Hu, Xiaoqi Wang, Kai Wang, Guiqin Zhang, Feiyong Chen, Tian Chen, Shuiyuan Cheng

    Published 2025-07-01
    “…Source inversion optimization using sensor observations is a key method for rapidly and accurately identifying unknown source parameters (source strength and location) in abrupt hazardous gas leaks. …”
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  18. 58

    Control optimization for permanent magnet synchronous generators in multi-source power systems by LI Lingyun, LIU Weizhi, WANG Yongxiang, LIU Yang

    Published 2024-11-01
    “…The results demonstrate that the proposed optimization method for the control of PMSGs tailored to multi-source power transmission systems achieves superior control performance by increasing the rate of disturbance inhibition, ensuring the stability of the DC-side voltage, and mitigating adverse impacts of complex conditions on the generators.…”
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  19. 59

    Optimal Management of High-Voltage Line Congestions Using Power Source Redispatching by Paweł Pijarski, Adrian Belowski, Ľubomír Beňa, Tomasz Binkowski, Bartłomiej Mroczek

    Published 2025-06-01
    “…The combination of the power flow tracking method and metaheuristic optimization allows for the effective elimination of line overloads. …”
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    Optimal Design of Interior Permanent Magnet Synchronous Motor Considering Various Sources of Uncertainty by Giacomo Guidotti, Dario Barri, Federico Soresini, Massimiliano Gobbi

    Published 2025-02-01
    “…Different designs of a 48 slot–8 pole motor are simulated with finite element analysis, then the outputs are used to train artificial neural networks that are employed to find the optimal design with different approaches. The method incorporates an innovative use of the neural network-based variance estimation (NNVE) technique to efficiently calculate the standard deviation of the objective functions. …”
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