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Yoga Sasmita, Heri Kuswanto and Dedy Dwi Prastyo
Standard time-series modeling requires the stability of model parameters over time. The instability of model parameters is often caused by structural breaks, leading to the formation of nonlinear models. A state-dependent model (SDM) is a more general an...
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Anqing Wang, Longwei Li, Haoliang Wang, Bing Han and Zhouhua Peng
In this paper, a swarm trajectory-planning method is proposed for multiple autonomous surface vehicles (ASVs) in an unknown and obstacle-rich environment. Specifically, based on the point cloud information of the surrounding environment obtained from loc...
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Mohammad Barooni and Deniz Velioglu Sogut
The design and optimization of floating offshore wind turbines (FOWTs) pose significant challenges, stemming from the complex interplay among aerodynamics, hydrodynamics, structural dynamics, and control systems. In this context, this study introduces an...
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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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Yufei Wang, Honghai Zhang, Zongbei Shi, Jinlun Zhou and Wenquan Liu
General aviation accidents have complex interactions and influences within them that cannot be simply explained and predicted by linear models. This study is based on chaos theory and uses general aviation accident data to conduct research on different t...
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Juan D. Borrero and Jesus Mariscal
Efforts across diverse domains like economics, energy, and agronomy have focused on developing predictive models for time series data. A spectrum of techniques, spanning from elementary linear models to intricate neural networks and machine learning algo...
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Saad Sh. Sammen, Mohammad Ehteram, Zohreh Sheikh Khozani and Lariyah Mohd Sidek
Predicting reservoir water levels helps manage droughts and floods. Predicting reservoir water level is complex because it depends on factors such as climate parameters and human intervention. Therefore, predicting water level needs robust models. Our st...
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Lan Luo, Yanjun Zhang, Wenxun Dong, Jinglin Zhang and Liping Zhang
Water quality prediction is an important part of water pollution prevention and control. Using a long short-term memory (LSTM) neural network to predict water quality can solve the problem that comprehensive water quality models are too complex and diffi...
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Cuicui Li and Wenliang Wu
Understanding the evolution characteristics and driving mechanisms of eutrophic lake ecosystems, especially over long time scales, remains a challenge. Little research on lake ecosystem mutation has been conducted using long-term time series data. In thi...
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Po-Wei Li, Shenghan Hu and Mengyao Zhang
This study applies the space?time generalized finite difference scheme to solve nonlinear dispersive shallow water waves described by the modified Camassa?Holm equation, the modified Degasperis?Procesi equation, the Fornberg?Whitham equation, and its mod...
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