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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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Michal Juszczyk
Analyses of efficiency are vital for planning and monitoring the duration and costs of construction works, as well as the entire construction project. This paper introduces a combined quantitative (probabilistic) and qualitative (machine learning-based) ...
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Zhehu Yuan, Yinqi Sun and Dennis Shasha
Database and data structure research can improve machine learning performance in many ways. One way is to design better algorithms on data structures. This paper combines the use of incremental computation as well as sequential and probabilistic filterin...
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Aristeidis Karras, Christos Karras, Konstantinos C. Giotopoulos, Dimitrios Tsolis, Konstantinos Oikonomou and Spyros Sioutas
Federated learning (FL) has emerged as a promising technique for preserving user privacy and ensuring data security in distributed machine learning contexts, particularly in edge intelligence and edge caching applications. Recognizing the prevalent chall...
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Igor Masich, Natalya Rezova, Guzel Shkaberina, Sergei Mironov, Mariya Bartosh and Lev Kazakovtsev
A number of real-world problems of automatic grouping of objects or clustering require a reasonable solution and the possibility of interpreting the result. More specific is the problem of identifying homogeneous subgroups of objects. The number of group...
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Khrystyna Zub, Pavlo Zhezhnych and Christine Strauss
In this paper, we investigate the methods used to evaluate the admission chances of higher education institutions? (HEI) entrants as a crucial factor that directly influences the admission efficiency, quality of education results, and future students? li...
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Roberto Vega, Leonardo Flores and Russell Greiner
Accurate forecasts of the number of newly infected people during an epidemic are critical for making effective timely decisions. This paper addresses this challenge using the SIMLR model, which incorporates machine learning (ML) into the epidemiological ...
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Olga V. Okhlupina,Dmitry S. Murashko
Pág. 17 - 20
Among the common methods of combating spam, a special place is occupied by a probabilistic machine learning algorithm, which is based on the well-known Bayes theorem. The so-called "naive" Bayesian classifier establishes the class of the document by dete...
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Farahnaz Soleimani and Donya Hajializadeh
Optimizing the serviceability of highway bridges is a fundamental prerequisite to provide proper infrastructure safety and emergency responses after natural hazards such as an earthquake. In this regard, fragility and resilience assessment have emerged a...
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Alireza Rezazadeh, Yasamin Jafarian and Ali Kord
Image classification is widely used to build predictive models for breast cancer diagnosis. Most existing approaches overwhelmingly rely on deep convolutional networks to build such diagnosis pipelines. These model architectures, although remarkable in p...
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