|
|
|
|
|
Carlos Alfonso Zafra-Mejía, Hugo Alexander Rondón-Quintana and Carlos Felipe Urazán-Bonells
The objective of this paper is to use autoregressive, integrated, and moving average (ARIMA) and transfer function ARIMA (TFARIMA) models to analyze the behavior of the main water quality parameters in the initial components of a drinking water supply sy...
ver más
|
|
|
|
|
|
|
|
|
|
|
Hao Sun, Zile Jia, Meng Zhao, Jiayuan Tian, Dan Liu and Yifei Wang
The current lack of a high-precision, real-time model applicable to the control optimization process of heat exchange systems, especially the difficulty in determining the overall heat transfer coefficient K of heat exchanger operating parameters in real...
ver más
|
|
|
|
|
|
|
|
|
|
|
Florent Grotto, Oscar Peta, Christophe Bouvet, Bruno Castanié and Joël Serra
Airworthiness certification requires proof of structure strength, which is performed generally through a building block approach. To achieve this, representative intermediate-scale experiments generated by test benches are, in general, needed, in additio...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yifei Xu, Te Li, Min Xu, Ling Tan and Shuanghe Shen
Climate change exerts significant impacts on regional agricultural production. This study assesses the implications of climate change on winter wheat yields in the Huang-Huai-Hai Plain (3H Plain), utilizing bias-corrected climate projections from the Cou...
ver más
|
|
|
|
|
|
|
|
|
|
|
Zhenyu Yin, Feiqing Zhang, Guangyuan Xu, Guangjie Han and Yuanguo Bi
Confronting the challenge of identifying unknown fault types in rolling bearing fault diagnosis, this study introduces a multi-scale bearing fault diagnosis method based on transfer learning. Initially, a multi-scale feature extraction network, MBDCNet, ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Baoyu Fan, Han Ma, Yue Liu and Xiaochen Yuan
With the growth of data in the real world, datasets often encounter the problem of long-tailed distribution of class sample sizes. In long-tailed image recognition, existing solutions usually adopt a class rebalancing strategy, such as reweighting based ...
ver más
|
|
|
|
|
|
|
|
|
|
|
George Tzougas and Konstantin Kutzkov
We developed a methodology for the neural network boosting of logistic regression aimed at learning an additional model structure from the data. In particular, we constructed two classes of neural network-based models: shallow?dense neural networks with ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Hongmei Zhang, Zhijie Li, Zishang Yang, Chenhui Zhu, Yinhai Ding, Pengchang Li and Xun He
Real-time knowledge of kernel breakage during corn harvesting plays a significant role in the adjustment of operational parameters of corn kernel harvesters. (1) Transfer learning by initializing the DenseNet121 network with pre-trained weights for train...
ver más
|
|
|
|
|
|
|
|
|
|
|
Mengting Zou, Jun Ma, Xin Xiong and Rong Li
To investigate the vibration properties in healthy and fault conditions of planetary gearboxes, a phenomenological model is constructed to present the vibration spectrum structure. First, the effects of the base deflection of the gear fillet and the flex...
ver más
|
|
|
|
|
|
|
|
|
|
|
Ziyu Guo, Jing Li, Shaotao Zhu and Yufeng Zhang
The dynamic vibration absorber (DVA) is widely used in engineering models with complex vibration modes. The research on the stability and periodic motions of the DVA model plays an important role in revealing its complex vibration modes and energy transf...
ver más
|
|
|
|
|
|