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Zhaoxuan Liu and Wenjie Luo
In recommendation models, bias can distort the distribution of user-generated data, leading to inaccurate representation of user preferences. Failure to filter out biased data can result in significant learning errors, ultimately reducing the accuracy of...
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Yixuan Li, Charalampos Stasinakis and Wee Meng Yeo
Supply Chain Finance (SCF) has gradually taken on digital characteristics with the rapid development of electronic information technology. Business audit information has become more abundant and complex, which has increased the efficiency and increased t...
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Matteo Gentilucci and Gilberto Pambianchi
The reconstruction of daily precipitation data is a much-debated topic of great practical use, especially when weather stations have missing data. Missing data are particularly numerous if rain gauges are poorly maintained by their owner institutions and...
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Iskander Abroug, Reine Matar and Nizar Abcha
The understanding of the occurrence of extreme waves is crucial to simulate the growth of waves in coastal regions. Laboratory experiments were performed to study the spatial evolution of the statistics of group-focused waves that have a relatively broad...
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Adriano Beluco, Denise L. Bandeira and Alexandre Beluco
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Sungwon Kim and Vijay P. Singh
The objective of this study is to develop artificial neural network (ANN) models, including multilayer perceptron (MLP) and Kohonen self-organizing feature map (KSOFM), for spatial disaggregation of areal rainfall in the Wi-stream catchment, an Internati...
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Youngmin Seo, Yunyoung Choi and Jeongwoo Choi
This paper proposes a river stage modeling approach combining maximal overlap discrete wavelet transform (MODWT), support vector machines (SVMs) and genetic algorithm (GA). The MODWT decomposes original river stage time series into sub-time series (detai...
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Youngmin Seo, Yunyoung Choi, Jeongwoo Choi
Pág. 1 - 24
This paper proposes a river stage modeling approach combining maximal overlap discrete wavelet transform (MODWT), support vector machines (SVMs) and genetic algorithm (GA). The MODWT decomposes original river stage time series into sub-time series (detai...
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K. CHRONOPOULOS,A. KAMOUTSIS,A. MATSOUKIS,E. MANOLI
In this research, an artificial neural network model (ANN) was applied to estimate the thermal comfort conditions in the mountainous regions of Gerania (MG) and of Nafpaktia (MN) in Greece. Air temperature and relative humidity were recorded from June to...
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Mohammad S. Islam, Shahid Husain, Jawed Mustafa and Yuantong Gu
The main challenge of the health risk assessment of the aerosol transport and deposition to the lower airways is the high computational cost. A standard large-scale airway model needs a week to a month of computational time in a high-performance computin...
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Mohammad Zounemat-Kermani, Youngmin Seo, Sungwon Kim, Mohammad Ali Ghorbani, Saeed Samadianfard, Shabnam Naghshara, Nam Won Kim and Vijay P. Singh
This study evaluates standalone and hybrid soft computing models for predicting dissolved oxygen (DO) concentration by utilizing different water quality parameters. In the first stage, two standalone soft computing models, including multilayer perceptron...
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A. L. Labajo,J. L. Labajo
A forecasting model for the mean monthly maximum temperatures (TMaxMean) using an artificial neuronal network (ANN) of the multilayer perceptron type (Multilayer Perceptron, MLP) has been developed. This model forecast the TMaxMean variable one month ahe...
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Der-Chang Lo, Chih-Chiang Wei and En-Ping Tsai
This paper presents artificial neural network (ANN)-based models for forecasting precipitation, in which the training parameters are adjusted using a parameter automatic calibration (PAC) approach. A classical ANN-based model, the multilayer perceptron (...
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Junhao Wu and Zhaocai Wang
Clean water is an indispensable essential resource on which humans and other living beings depend. Therefore, the establishment of a water quality prediction model to predict future water quality conditions has a significant social and economic value. In...
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Muhammad Turki Alshurideh,Said Abdelrahim Salloum,Barween Al Kurdi,Azza Abdel Monem,Khaled Shaalan
Pág. pp. 157 - 183
There is a widespread use of Internet technology in the present times, because of which universities are making investments in Mobile learning to augment their position in the face of extensive competition and also to enhance their students? learning exp...
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Bahram Choubin,Arash Malekian,Mohammad Gloshan
Pág. 121 - 128
Climate modeling and prediction is important in water resources management, especially in arid and semi-arid regions that frequently suffer further from water shortages. The Maharlu-Bakhtegan basin, with an area of 31?000 km2 is a semi-arid and arid regi...
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Osman Isa Çelik, Gürcan Büyüksalih and Cem Gazioglu
The spatial and spectral information brought by the Very High Resolution (VHR) and multispectral satellite images present an advantage for Satellite-Derived Bathymetry (SDB), especially in shallow-water environments with dense wave patterns. This work fo...
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Oscar Ulises Espinosa Barcenas, Jose Gabriel Quijada Pioquinto, Ekaterina Kurkina and Oleg Lukyanov
The aircraft conceptual design step requires a substantial number of aerodynamic configuration evaluations. Since the wing is the main aircraft lifting element, the focus is on solving direct and reverse design problems. The former could be solved using ...
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Yuki Wakatsuki, Hideaki Nakane and Tempei Hashino
The increasing frequency of devastating floods from heavy rainfall?associated with climate change?has made river stage prediction more important. For steep, forest-covered mountainous watersheds, deep-learning models may improve prediction of river stage...
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Joseph Isabona, Agbotiname Lucky Imoize, Stephen Ojo, Olukayode Karunwi, Yongsung Kim, Cheng-Chi Lee and Chun-Ta Li
Modern cellular communication networks are already being perturbed by large and steadily increasing mobile subscribers in high demand for better service quality. To constantly and reliably deploy and optimally manage such mobile cellular networks, the ra...
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