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Yuriy Povstenko, Tamara Kyrylych, Bozena Wozna-Szczesniak and Andrzej Yatsko
The central-symmetric time-fractional heat conduction equation with heat absorption is investigated in a solid with a spherical hole under time-harmonic heat flux at the boundary. The problem is solved using the auxiliary function, for which the Robin-ty...
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Haibo Chu, Zhuoqi Wang and Chong Nie
Accurate and reliable monthly streamflow prediction plays a crucial role in the scientific allocation and efficient utilization of water resources. In this paper, we proposed a prediction framework that integrates the input variable selection method and ...
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Shubin Zhang, Peifang Dai, Ning Li and Yanbo Chen
Integrated circuits suffer severe deterioration due to single-event upsets (SEUs) in irradiated environments. Spin-transfer torque magnetic random-access memory (STT-MRAM) appears to be a promising candidate for next-generation memory as it shows promisi...
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Hu Cai, Jiafu Wan and Baotong Chen
Traditional capacity forecasting algorithms lack effective data interaction, leading to a disconnection between the actual plan and production. This paper discusses the multi-factor model based on a discrete manufacturing workshop and proposes a digital ...
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Yin Tang, Lizhuo Zhang, Dan Huang, Sha Yang and Yingchun Kuang
In view of the current problems of complex models and insufficient data processing in ultra-short-term prediction of photovoltaic power generation, this paper proposes a photovoltaic power ultra-short-term prediction model named HPO-KNN-SRU, based on a S...
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Rujia Li, Yadong Li, Weibo Qin, Arzlan Abbas, Shuang Li, Rongbiao Ji, Yehui Wu, Yiting He and Jianping Yang
This research tackles the intricate challenges of detecting densely distributed maize leaf diseases and the constraints inherent in YOLO-based detection algorithms. It introduces the GhostNet_Triplet_YOLOv8s algorithm, enhancing YOLO v8s by integrating t...
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Yongen Lin, Dagang Wang, Tao Jiang and Aiqing Kang
Reliable streamflow forecasting is a determining factor for water resource planning and flood control. To better understand the strengths and weaknesses of newly proposed methods in streamflow forecasting and facilitate comparisons of different research ...
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Omar Serghini, Hayat Semlali, Asmaa Maali, Abdelilah Ghammaz and Salvatore Serrano
Spectrum sensing is an essential function of cognitive radio technology that can enable the reuse of available radio resources by so-called secondary users without creating harmful interference with licensed users. The application of machine learning tec...
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Guangyin Lu, Dongxing Zhang, Shujin Cao, Yihuai Deng, Gang Xu, Yihu Liu, Ziqiang Zhu and Peng Chen
In large-scale potential field data inversion, constructing the kernel matrix is a time-consuming problem with large memory requirements. Therefore, a spherical planting inversion of Gravity Recovery and Interior Laboratory (GRAIL) data is proposed using...
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Diego Renza and Dora Ballesteros
CNN models can have millions of parameters, which makes them unattractive for some applications that require fast inference times or small memory footprints. To overcome this problem, one alternative is to identify and remove weights that have a small im...
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