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Lilai Jin, Sarah J. Higgins, James A. Thompson, Michael P. Strager, Sean E. Collins and Jason A. Hubbart
Saturated hydraulic conductivity (Ksat) is a hydrologic flux parameter commonly used to determine water movement through the saturated soil zone. Understanding the influences of land-use-specific Ksat on the model estimation error of water balance compon...
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Luis Zuloaga-Rotta, Rubén Borja-Rosales, Mirko Jerber Rodríguez Mallma, David Mauricio and Nelson Maculan
The forecasting of presidential election results (PERs) is a very complex problem due to the diversity of electoral factors and the uncertainty involved. The use of a hybrid approach composed of techniques such as machine learning (ML) and Simulation in ...
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Francisca Lanai Ribeiro Torres, Luana Medeiros Marangon Lima, Michelle Simões Reboita, Anderson Rodrigo de Queiroz and José Wanderley Marangon Lima
Streamflow forecasting plays a crucial role in the operational planning of hydro-dominant power systems, providing valuable insights into future water inflows to reservoirs and hydropower plants. It relies on complex mathematical models, which, despite t...
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Felipe Duque, Greg O?Donnell, Yanli Liu, Mingming Song and Enda O?Connell
Polders are low-lying areas located in deltas, surrounded by embankments to prevent flooding (river or tidal floods). They rely on pumping systems to remove water from the inner rivers (artificial rivers inside the polder area) to the outer rivers, espec...
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Jeonghoon Lee, Jeonghyeon Choi, Jiyu Seo, Jeongeun Won and Sangdan Kim
In the context of hydrological model calibration, observational data play a central role in refining and evaluating model performance and uncertainty. Among the critical factors, the length of the data records and the associated climatic conditions are p...
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Muhammad Irfan, Seyed Shahrestani and Mahmoud Elkhodr
Dementia, including Alzheimer?s Disease (AD), is a complex condition, and early detection remains a formidable challenge due to limited patient records and uncertainty in identifying relevant features. This paper proposes a machine learning approach to a...
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Linling Wang, Xiaoyan Xu, Bing Han and Huapeng Zhang
In this paper, multiple autonomous underwater vehicle (multi-AUV) formation control with obstacle avoidance ability in 3D complex underwater environments based on an event-triggered model predictive control (EMPC) is proposed. Firstly, multi-AUV motion m...
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Haizhou Cao, Jing Yang, Xuemeng Zhao, Tiechui Yao, Jue Wang, Hui He and Yangang Wang
The penetration of photovoltaic (PV) energy has gained a significant increase in recent years because of its sustainable and clean characteristics. However, the uncertainty of PV power affected by variable weather poses challenges to an accurate short-te...
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Wenyu Cao, Benbo Sun and Pengxiao Wang
Rapidly developed deep learning methods, widely used in various fields of civil engineering, have provided an efficient option to reduce the computational costs and improve the predictive capabilities. However, it should be acknowledged that the applicat...
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Apostolos Ampountolas
This study analyzes the transmission of market uncertainty on key European financial markets and the cryptocurrency market over an extended period, encompassing the pre-, during, and post-pandemic periods. Daily financial market indices and price observa...
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