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Timothy O. Hodson, Keith J. Doore, Terry A. Kenney, Thomas M. Over and Muluken B. Yeheyis
Streamflow is one of the most important variables in hydrology, but it is difficult to measure continuously. As a result, nearly all streamflow time series are estimated from rating curves that define a mathematical relationship between streamflow and so...
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Leon Kopitar, Iztok Fister, Jr. and Gregor Stiglic
Introduction: Type 2 diabetes mellitus is a major global health concern, but interpreting machine learning models for diagnosis remains challenging. This study investigates combining association rule mining with advanced natural language processing to im...
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Zichen Yan, Jianzhong Sun, Yang Yi, Caiqiong Yang and Jingbo Sun
Data analysis is an important part of aero engine health management. In order to complete accurate condition monitoring, it is necessary to establish more effective analysis tools. Therefore, an integrated algorithm library dedicated for engine anomaly d...
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Andrei Velichko, Maksim Belyaev, Yuriy Izotov, Murugappan Murugappan and Hanif Heidari
Entropy measures are effective features for time series classification problems. Traditional entropy measures, such as Shannon entropy, use probability distribution function. However, for the effective separation of time series, new entropy estimation me...
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Dmitry Lukyanenko
The paper proposes a parallel algorithm for solving large overdetermined systems of linear algebraic equations with a dense matrix. This algorithm is based on the use of a modification of the conjugate gradient method, which is able to take into account ...
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Mayur Kishor Shende, Sinan Q. Salih, Neeraj Dhanraj Bokde, Miklas Scholz, Atheer Y. Oudah and Zaher Mundher Yaseen
Climate change has contributed substantially to the weather and land characteristic phenomena. Accurate time series forecasting for climate and land parameters is highly essential in the modern era for climatologists. This paper provides a brief introduc...
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Catherine Birney, Ben Young, Mo Li, Melissa Conner, Jacob Specht and Wesley W. Ingwersen
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Amirata Ghorbani, Dina Berenbaum, Maor Ivgi, Yuval Dafna and James Y. Zou
Interpretability is becoming an active research topic as machine learning (ML) models are more widely used to make critical decisions. Tabular data are one of the most commonly used modes of data in diverse applications such as healthcare and finance. Mu...
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Ming Zhang and Bolin Lan
Urban science research and the research on megaregions share a common interest in the system of cities and its implications for world urbanization and sustainability. The two lines of inquiry currently remain largely separate efforts. This study aims to ...
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Andrei Gorchakov
Pág. 1 - 5
When developing parallel methods for solving many numerical methods for solving applied problems, in particular the branch-and-bound method, the problem of load balancing arises. The choice of implementation options at the moment has been proposed quite ...
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