|
|
|
|
|
Haibo Chu, Zhuoqi Wang and Chong Nie
Accurate and reliable monthly streamflow prediction plays a crucial role in the scientific allocation and efficient utilization of water resources. In this paper, we proposed a prediction framework that integrates the input variable selection method and ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Sabrina De Nardi, Claudio Carnevale, Sara Raccagni and Lucia Sangiorgi
Models are a core element in performing local estimation of the climate change input. In this work, a novel approach to perform a fast downscaling of global temperature anomalies on a regional level is presented. The approach is based on a set of data-dr...
ver más
|
|
|
|
|
|
|
|
|
|
|
Li Li and Kyung Soo Jun
River flood routing computes changes in the shape of a flood wave over time as it travels downstream along a river. Conventional flood routing models, especially hydrodynamic models, require a high quality and quantity of input data, such as measured hyd...
ver más
|
|
|
|
|
|
|
|
|
|
|
Deepanjal Shrestha, Tan Wenan, Deepmala Shrestha, Neesha Rajkarnikar and Seung-Ryul Jeong
This study introduces a data-driven and machine-learning approach to design a personalized tourist recommendation system for Nepal. It examines key tourist attributes, such as demographics, behaviors, preferences, and satisfaction, to develop four sub-mo...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
J. D. Tamayo-Quintero, J. B. Gómez-Mendoza and S. V. Guevara-Pérez
Objective: This study aims to introduce and assess a novel AI-driven tool developed for the classification of orthodontic arch shapes into square, ovoid, and tapered categories. Methods: Between 2016 and 2019, we collected 450 digital dental models. Appl...
ver más
|
|
|
|
|
|
|
|
|
|
|
Juan Ma, Qiang Yang, Mingzhi Zhang, Yao Chen, Wenyi Zhao, Chengyu Ouyang and Dongping Ming
Accurately predicting landslide deformation based on monitoring data is key to successful early warning of landslide disasters. Landslide displacement?time curves offer an intuitive reflection of the landslide motion process and deformation predictions o...
ver más
|
|
|
|
|
|
|
|
|
|
|
Seyed Mohammad Hashemi, Ruxandra Mihaela Botez and Georges Ghazi
Accurate aircraft trajectory prediction is fundamental for enhancing air traffic control systems, ensuring a safe and efficient aviation transportation environment. This research presents a detailed study on the efficacy of the Random Forest (RF) methodo...
ver más
|
|
|
|
|
|
|
|
|
|
|
Hugo Valayer, Nathalie Bartoli, Mauricio Castaño-Aguirre, Rémi Lafage, Thierry Lefebvre, Andrés F. López-Lopera and Sylvain Mouton
In aerodynamics, characterizing the aerodynamic behavior of aircraft typically requires a large number of observation data points. Real experiments can generate thousands of data points with suitable accuracy, but they are time-consuming and resource-int...
ver más
|
|
|
|
|
|