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Yadong Zhou, Zhenchao Teng, Linlin Chi and Xiaoyan Liu
Based on the unit life and death technology, the dynamic evolution process of soil loss is considered, and a pipe-soil nonlinear coupling model of buried pipelines passing through the collapse area is constructed. The analysis shows that after the third ...
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Tianao Qin, Ruixin Chen, Rufu Qin and Yang Yu
Time series prediction is an effective tool for marine scientific research. The Hierarchical Temporal Memory (HTM) model has advantages over traditional recurrent neural network (RNN)-based models due to its online learning and prediction capabilities. G...
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Gulsum Alicioglu and Bo Sun
Deep learning (DL) models have achieved state-of-the-art performance in many domains. The interpretation of their working mechanisms and decision-making process is essential because of their complex structure and black-box nature, especially for sensitiv...
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May Alsaidi, Nadim Obeid, Nailah Al-Madi, Hazem Hiary and Ibrahim Aljarah
Autism spectrum disorder (ASD) is a developmental disorder that encompasses difficulties in communication (both verbal and non-verbal), social skills, and repetitive behaviors. The diagnosis of autism spectrum disorder typically involves specialized proc...
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Haohao Guo, Tianxiang Xiang, Yancheng Liu, Qiaofen Zhang, Yi Wei and Fengkui Zhang
This paper proposes a new method for compensating current measurement errors in shipboard permanent magnet propulsion motors. The method utilizes cascade decoupling second-order generalized integrators (SOGIs) and adaptive linear neurons (ADALINEs) as th...
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Rohan S. Sharma and Serhat Hosder
The intent of this work was to investigate the feasibility of developing machine learning models for calculating values of airplane configuration design variables when provided time-series, mission-informed performance data. Shallow artificial neural net...
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Zhen Liu, Qifeng Yang, Anlue Wang and Xingyu Gu
In the process of driving in an underground interchange, drivers are faced with many challenges, such as being in a closed space, visual changes alternating between light and dark conditions, complex road conditions in the confluence section, and dense s...
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Michiel van der Vlag, Lionel Kusch, Alain Destexhe, Viktor Jirsa, Sandra Diaz-Pier and Jennifer S. Goldman
Global neural dynamics emerge from multi-scale brain structures, with nodes dynamically communicating to form transient ensembles that may represent neural information. Neural activity can be measured empirically at scales spanning proteins and subcellul...
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Martina Saletta and Claudio Ferretti
Deep neural networks have proven to be able to learn rich internal representations, including for features that can also be used for different purposes than those the networks are originally developed for. In this paper, we are interested in exploring su...
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Andreas G. Savva, Theocharis Theocharides and Chrysostomos Nicopoulos
Nowadays, due to their excellent prediction capabilities, the use of artificial neural networks (ANNs) in software has significantly increased. One of the most important aspects of ANNs is robustness. Most existing studies on robustness focus on adversar...
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