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Li, Zi-Yuan; Qian, Zhen; He, Jie-Han; He, Wei; Wu, Cheng-Xin; Cai, Xun-Ye; You, Zheng-Yun; Zhang, Yu-Mei; Luo, Wu-Ming
Nuclear science and techniques, 07/2022, Letnik: 33, Številka: 7Journal Article
The precise vertex reconstruction for large liquid scintillator detectors is essential. A novel machine learning-based method was successfully developed to reconstruct an event vertex in JUNO. In this study, the performance of machine learning-based vertex reconstruction was further improved by optimizing the input images of neural networks. By separating the information of different types of PMTs and adding the information of the second hit of PMTs, the vertex resolution was improved by approximately 9.4 % at 1 MeV and 9.8 % at 11 MeV.
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Dostop do baze podatkov JCR je dovoljen samo uporabnikom iz Slovenije. Vaš trenutni IP-naslov ni na seznamu dovoljenih za dostop, zato je potrebna avtentikacija z ustreznim računom AAI.
Leto | Faktor vpliva | Izdaja | Kategorija | Razvrstitev | ||||
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JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
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Povezave do osebnih bibliografij avtorjev | Povezave do podatkov o raziskovalcih v sistemu SICRIS |
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Vir: Osebne bibliografije
in: SICRIS
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