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Haoran Liu, Kehui Xu, Bin Li, Ya Han and Guandong Li
Machine learning classifiers have been rarely used for the identification of seafloor sediment types in the rapidly changing dredge pits for coastal restoration. Our study uses multiple machine learning classifiers to identify the sediment types of the C...
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Yahui Hu, Jiaqi Yan, Ertai Cao, Yimeng Yu, Haiming Tian and Heyuan Huang
The statistical analysis of civil aircraft accidents reveals that the highest incidence of mishaps occurs during the approach and landing stages. Predominantly, these accidents are marked by abnormal energy states, leading to critical situations like sta...
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Futo Ueda, Hiroto Tanouchi, Nobuyuki Egusa and Takuya Yoshihiro
River water-level prediction is crucial for mitigating flood damage caused by torrential rainfall. In this paper, we attempt to predict river water levels using a deep learning model based on radar rainfall data instead of data from upstream hydrological...
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Jiaming Li, Ning Xie and Tingting Zhao
In recent years, with the rapid advancements in Natural Language Processing (NLP) technologies, large models have become widespread. Traditional reinforcement learning algorithms have also started experimenting with language models to optimize training. ...
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Jiahao Chen, Jiaxin Li, Deqian Zheng, Qianru Zheng, Jiayi Zhang, Meimei Wu and Chaosai Liu
The multi-field coupling of grain piles in grain silos is a focal point of research in the field of grain storage. The porosity of grain piles is a critical parameter that affects the heat and moisture transfer in grain piles. To investigate the distribu...
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Huang Feng and Yu Zhang
Extensive research in predicting annual passenger throughput has been conducted, aiming at providing decision support for airport construction, aircraft procurement, resource management, flight scheduling, etc. However, how airport operational throughput...
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Changchang Li, Botao Xu, Zhiwei Chen, Xiaoou Huang, Jing (Selena) He and Xia Xie
University students, as a special group, face multiple psychological pressures and challenges, making them susceptible to social anxiety disorder. However, there are currently no articles using machine learning algorithms to identify predictors of social...
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Jianlei Qiao, Yonglu Lv, Yucai Feng, Chang Liu, Yi Zhang, Jinying Li, Shuang Liu and Xiaohui Weng
At present, the electronic nose has became a new technology for the rapid detection of pesticides. However, the technique may misidentify them for samples that have not been involved in training. Therefore, a hybrid model based on unsupervised and superv...
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Subin Kim, Heejin Hwang, Keunyeong Oh and Jiuk Shin
The seismically deficient column details in existing reinforced concrete buildings affect the overall behavior of the building depending on the failure type of the column. The purpose of this study is to develop and validate a machine-learning-based pred...
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Nirmal Acharya, Padmaja Kar, Mustafa Ally and Jeffrey Soar
Significant clinical overlap exists between mental health and substance use disorders, especially among women. The purpose of this research is to leverage an AutoML (Automated Machine Learning) interface to predict and distinguish co-occurring mental hea...
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