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Bahareh Kalantar, Husam A. H. Al-Najjar, Biswajeet Pradhan, Vahideh Saeidi, Alfian Abdul Halin, Naonori Ueda and Seyed Amir Naghibi
Assessment of the most appropriate groundwater conditioning factors (GCFs) is essential when performing analyses for groundwater potential mapping. For this reason, in this work, we look at three statistical factor analysis methods?Variance Inflation Fac...
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Ying-Hsun Lai, Shin-Yeh Chen, Wen-Chi Chou, Hua-Yang Hsu and Han-Chieh Chao
Federated learning trains a neural network model using the client?s data to maintain the benefits of centralized model training while maintaining their privacy. However, if the client data are not independently and identically distributed (non-IID) becau...
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Angel E. Muñoz-Zavala, Jorge E. Macías-Díaz, Daniel Alba-Cuéllar and José A. Guerrero-Díaz-de-León
This paper reviews the application of artificial neural network (ANN) models to time series prediction tasks. We begin by briefly introducing some basic concepts and terms related to time series analysis, and by outlining some of the most popular ANN arc...
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Xinmin Li, Yingkun Wei, Jiahui Li, Wenwen Duan, Xiaoqiang Zhang and Yi Huang
Object detection in unmanned aerial vehicle (UAV) images has become a popular research topic in recent years. However, UAV images are captured from high altitudes with a large proportion of small objects and dense object regions, posing a significant cha...
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Ahmed Yosri, Maysara Ghaith, Mohamed Ismaiel Ahmed and Wael El-Dakhakhni
The efficient management and remediation of contaminated fractured aquifers necessitate an accurate prediction of the spatial distribution of contaminant concentration within the system. Related existing analytical solutions are only applicable to single...
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Erik Kralj, Peter Kumer and Cécil J. W. Meulenberg
The escalating frequency and severity of climate-related hazards in the Mediterranean, particularly in the historic town of Piran, Slovenia, underscore the critical need for enhanced coastal flood prediction and efficient early warning systems. This stud...
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Chi-Min Chiu, Laurence Zsu-Hsin Chuang, Wei-Liang Chuang, Li-Chung Wu, Ching-Jer Huang and Yinglong Joseph Zhang
This study aims to establish a comprehensive workflow for developing emergency response plans for both actual and scenario oil spill incidents in the Taiwan waters while addressing the resource allocation for oil spill containment as well. This workflow ...
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Jingyun Gui, Ignacio Pérez-Rey, Miao Yao, Fasuo Zhao and Wei Chen
Spatial landslide susceptibility assessment is a fundamental part of landslide risk management and land-use planning. The main objective of this study is to apply the Credal Decision Tree (CDT), adaptive boosting Credal Decision Tree (AdaCDT), and random...
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Yan Jin, Yong Ge, Haoyu Fan, Zeshuo Li, Yaojie Liu and Yan Jia
Accurate spatial distribution of gridded gross domestic product (GDP) data is crucial for revealing regional disparities within administrative units, thus facilitating a deeper understanding of regional economic dynamics, industrial distribution, and urb...
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William Villegas-Ch, Joselin García-Ortiz and Angel Jaramillo-Alcazar
This paper investigated the importance of explainability in artificial intelligence models and its application in the context of prediction in Formula (1). A step-by-step analysis was carried out, including collecting and preparing data from previous rac...
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