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Niloufar Beikahmadi, Antonio Francipane and Leonardo Valerio Noto
Accurate precipitation estimation remains a challenge, though it is fundamental for most hydrological analyses. In this regard, this study aims to achieve two objectives. Firstly, we evaluate the performance of two precipitation products from the Integra...
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András Bóta and Lauren Gardner
Modeling the spread of infections in networks is a well-studied and important field of research. Most infection and diffusion models require a real value or probability at the edges of the network as an input, but this is rarely available in real-life ap...
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Qasem Abu Al-Haija
The determination of electric energy consumption is remarked as one of the most vital objectives for electrical engineers as it is highly essential in determining the actual energy demand made on the existing electricity supply. Therefore, it is importan...
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Yicheng Luo, Yajing Xu, Si Li, Qifeng Qian and Bo Xiao
Convolutional neural networks have achieved great success in analyzing potential features inside tropical cyclones (TCs) using satellite images for intensity estimation. However, due to the high similarity of visual features in TC images, it is still a c...
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Sina Keller, Raoul Gabriel and Johanna Guth
Average speed information, which is essential for routing applications, is often missing in the freely available OpenStreetMap (OSM) road network. In this contribution, we propose an estimation framework, including different machine learning (ML) models ...
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Yasha Zeinali and Brett A. Story
Structural degradation is an inevitable part of a structure?s service life. Detecting structural impairments and assessing their nature is a significant challenge. Degradations reduce structural system stiffness and subsequently affect system deformation...
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Yasha Zeinali, Brett A. Story
Pág. 1 - 19
Structural degradation is an inevitable part of a structure?s service life. Detecting structural impairments and assessing their nature is a significant challenge. Degradations reduce structural system stiffness and subsequently affect system deformation...
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Zhiheng Xu, Jee Eun Kang, Roger Chen
Pág. 809 - 826
This paper develops a random utility based estimation framework for the Household Activity Pattern Problem (HAPP). Based on the realization that outputs of complex activity-travel decisions form a continuous pattern in space-time dimension, the estimatio...
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Yeonjoo Kim, Eun-Sung Chung, Kwangjae Won and Kyungik Gil
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Yeonjoo Kim, Eun-Sung Chung, Kwangjae Won and Kyungik Gil
This study developed a robust parameter set (ROPS) selection framework for a rainfall-runoff model that considers multi-events using the Pareto optimum and minimax regret approach (MRA). The calibrated parameter sets based on the Nash-Sutcliffe coefficie...
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Sheng He, Geng Niu, Xuefeng Sang, Xiaozhong Sun, Junxian Yin and Heting Chen
Accurate and reliable discharge estimation plays an important role in water resource management as well as downstream applications such as ecosystem conservation and flood control. Recently, data-driven machine learning (ML) techniques showed seemingly i...
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Hailun Xia and Tianyang Zhang
Estimating the positions of human joints from monocular single RGB images has been a challenging task in recent years. Despite great progress in human pose estimation with convolutional neural networks (CNNs), a central problem still exists: the relation...
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Jabar H. Yousif, Saif N. Abdul Majeed and Fouad J. I. Al Azzawi
Quantity Surveying (QS) is a process concerned with controlling and managing the costs of construction projects. QS Measurement relies on sophisticated measurement rules that are understood by experienced practitioners. Traditional QS systems, such as st...
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Jiangtao Ji, Xiaofei Wang, Hao Ma, Fengxun Zheng, Yi Shi, Hongwei Cui and Shaoshuai Zhao
Chlorophyll a and b content (Cab) and leaf area index (LAI) are two key parameters of crops, and their quantitative inversions are important for growth monitoring and the field management of wheat. However, due to the close correlation between the spectr...
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Yanqiu Gao
The ensemble Kalman filter is often used in parameter estimation, which plays an essential role in reducing model errors. However, filter divergence is often encountered in an estimation process, resulting in the convergence of parameters to the improper...
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Vasco M. N. C. S. Vieira, Pavel Jurus, Emanuela Clementi and Marcos Mateus
Accurate estimates of the atmosphere–ocean fluxes of greenhouse gases and dimethyl sulphide (DMS) have great importance in climate change models. A significant part of these fluxes occur at the coastal ocean which, although much smaller than the op...
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Jiwon Son, Chankyu Son and Kwanjung Yee
Waverider is a hypersonic vehicle that improves the lift-to-drag ratio using the shockwave attached to the leading edge of the lifting surface. Owing to its superior aerodynamic performance, it exhibits a viable external configuration in hypersonic fligh...
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Min Young Yoo, Jung Heon Lee, Joo-Ho Choi, Jae Sung Huh and Woosuk Sung
This paper proposes a framework for accurately estimating the state-of-charge (SOC) and current sensor bias, with the aim of integrating it into urban air mobility (UAM) with hybrid propulsion. Considering the heightened safety concerns in an airborne en...
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Alvaro Arroyo Cebeira and Mariano Asensio Vicente
In this paper, we propose a nonlinear tracking solution for maneuvering aerial targets based on an adaptive interacting multiple model (IMM) framework and unscented Kalman filters (UKFs), termed as AIMM-UKF. The purpose is to obtain more accurate estimat...
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Yibo Zhang, Hao Sun, Fanhang Zhang, Baohua Zhang, Shutian Tao, Haitao Li, Kaijie Qi, Shaoling Zhang, Seishi Ninomiya and Yue Mu
To realize autonomous navigation and intelligent management in orchards, vehicles require real-time positioning and globally consistent mapping of surroundings with sufficient information. However, the unstructured and unstable characteristics of orchard...
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