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Guy Bates, Mario Beruvides and Clifford B. Fedler
A system dynamics approach to groundwater modeling suitable for groundwater management planning is presented for a basin-scale system. System dynamics techniques were used to develop a general model for estimating changes in net annual groundwater storag...
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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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Sipho G. Thango, Georgios A. Drosopoulos, Siphesihle M. Motsa and Georgios E. Stavroulakis
A methodology to predict key aspects of the structural response of masonry walls under blast loading using artificial neural networks (ANN) is presented in this paper. The failure patterns of masonry walls due to in and out-of-plane loading are complex d...
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Sai Wang, Guoping Fu, Yongduo Song, Jing Wen, Tuanqi Guo, Hongjin Zhang and Tuantuan Wang
The development of intelligent oceans requires exploration and an understanding of the various characteristics of the oceans. The emerging Internet of Underwater Things (IoUT) is an extension of the Internet of Things (IoT) to underwater environments, an...
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Sajjad E. Rasheed, Duaa Al-Jeznawi, Musab Aied Qissab Al-Janabi and Luís Filipe Almeida Bernardo
The structural stability of pipe pile foundations under seismic loading stands as a critical concern, demanding an accurate assessment of the maximum settlement. Traditionally, this task has been addressed through complex numerical modeling, accounting f...
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Ilia Zaznov, Julian Martin Kunkel, Atta Badii and Alfonso Dufour
This paper introduces a novel deep learning approach for intraday stock price direction prediction, motivated by the need for more accurate models to enable profitable algorithmic trading. The key problems addressed are effectively modelling complex limi...
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Wei Zhuang, Zhiheng Li, Ying Wang, Qingyu Xi and Min Xia
Predicting photovoltaic (PV) power generation is a crucial task in the field of clean energy. Achieving high-accuracy PV power prediction requires addressing two challenges in current deep learning methods: (1) In photovoltaic power generation prediction...
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Mingfei Wang, Xiangshu Kong, Feifei Shan, Wengang Zheng, Pengfei Ren, Jiaoling Wang, Chunling Chen, Xin Zhang and Chunjiang Zhao
Temperature has a significant impact on the production of edible mushrooms. The industrial production of edible mushrooms is committed to accurately maintaining the temperature inside the mushroom room within a certain range to achieve quality and effici...
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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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Nikolaos Bakas
Function approximation is a fundamental process in a variety of problems in computational mechanics, structural engineering, as well as other domains that require the precise approximation of a phenomenon with an analytic function. This work demonstrates...
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