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Showing 20 of 1,254 academic articles
Samira Pouyanfar, Saad B Sadiq, Yilin Yan, Haiman Tian et al. • ACM Computing Surveys
(2018)
The field of machine learning is witnessing its golden era as deep learning slowly becomes the leader in this domain. Deep learning uses multiple layers to represent the abstractions of data to build computational models. Some key enabler d...
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DOI: https://doi.org/10.1145/3234150
Ian Goodfellow, Yoshua Bengio, Aaron C. Courville • The MIT Press eBooks
(2016)
Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human c...
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DOI: https://doi.org/10.1016/b978-0-12-804291-5.00010-6
Kamel Arafet, Rafael Berlanga • Algorithms
(2021)
The generation of electricity through renewable energy sources increases every day, with solar energy being one of the fastest-growing. The emergence of information technologies such as Digital Twins (DT) in the field of the Internet of Thi...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/a14050156
Mohammed Javeed Zaki, Wagner Meira • Cambridge University Press eBooks
(2020)
The fundamental algorithms in data mining and machine learning form the basis of data science, utilizing automated methods to analyze patterns and models for all kinds of data in applications ranging from scientific discovery to business an...
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DOI: https://doi.org/10.1017/9781108564175
Luigi Capogrosso, Federico Cunico, Dong Seon Cheng, Franco Fummi et al. • IEEE Access
(2024)
The emergence of Tiny Machine Learning (TinyML) has positively revolutionized the field of Artificial Intelligence by promoting the joint design of resource-constrained IoT hardware devices and their learning-based software architectures. T...
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DOI: https://doi.org/10.1109/access.2024.3365349
Ahmed E. Radwan, David A. Wood, Ahmed A. Radwan • Journal of Rock Mechanics and Geotechnical Engineering
(2022)
Pore pressure is an essential parameter for establishing reservoir conditions, geological interpretation and drilling programs. Pore pressure prediction depends on information from various geophysical logs, seismic, and direct down-hole pre...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.jrmge.2022.01.012
Supriya D. Mehta, Dan Zhao, Stefan J. Green, Walter Agingu et al. • Frontiers in Cellular and Infection Microbiology
(2020)
Background: We determined the predictive accuracy of penile bacteria for incident BV in female sex partners. In this prospective cohort, we enrolled Kenyan men aged 18–35 and their female sex partners aged 16 and older. We assessed BV at ba...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fcimb.2020.00433
Ognjen Radišić-Aberger, Peter Burggräf, Fabian Steinberg, Alexander Becher et al. • Supply Chain Analytics
(2024)
By applying machine learning algorithms, predictive business process monitoring (PBPM) techniques provide an opportunity to counteract undesired outcomes of processes. An especially complex variation of business processes is the engineering...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.sca.2024.100087
Xin Qian, Yu Li, Xianghui Zhang, Heng Guo et al. • Frontiers in Cardiovascular Medicine
(2022)
BackgroundCardiovascular diseases (CVD) are currently the leading cause of premature death worldwide. Model-based early detection of high-risk populations for CVD is the key to CVD prevention. Thus, this research aimed to use machine learni...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fcvm.2022.854287
Róbert Skapinyecz • Machine Learning and Knowledge Extraction
(2026)
The paper presents a novel large language model-based neighbourhood search method for production scheduling using discrete-event simulation (DES) as the modelling and evaluation engine. The combination of large language models (LLMs) and DE...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/make8090284
Hao Yan, Xingao Li, Zhongliang Shi, Shuyuan Wang • IEEE Access
(2024)
Motion intent recognition research is one of the key challenges in achieving human-robot collaboration in rehabilitation robots. In the traditional method, intention recognition is performed based on the complete sEMG, however, due to the m...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2024.3447275
Federico Amato, Fabian Guignard, Sylvain Robert, Mikhail Kanevski • Scientific Reports
(2020)
Abstract As the role played by statistical and computational sciences in climate and environmental modelling and prediction becomes more important, Machine Learning researchers are becoming more aware of the relevance of their work to help ...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41598-020-79148-7
Younggill Son, Woongchul Choi • Batteries
(2024)
With the global surge in electric vehicle (EV) deployment, driven by enhanced environmental regulations and efforts to reduce transportation-related greenhouse gas emissions, managing the life cycle of Li-ion batteries becomes more critical...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/batteries10060191
Jeremy M. Watt, Reza Borhani, Aggelos K. Katsaggelos • Cambridge University Press eBooks
(2020)
With its intuitive yet rigorous approach to machine learning, this text provides students with the fundamental knowledge and practical tools needed to conduct research and build data-driven products. The authors prioritize geometric intuiti...
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DOI: https://doi.org/10.1017/9781108690935
Osvaldo Simeone • Cambridge University Press eBooks
(2022)
This self-contained introduction to machine learning, designed from the start with engineers in mind, will equip students with everything they need to start applying machine learning principles and algorithms to real-world engineering probl...
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DOI: https://doi.org/10.1017/9781009072205
Jichao Li, Xiaosong Du, Joaquim R. R. A. Martins • Progress in Aerospace Sciences
(2022)
Machine learning (ML) has been increasingly used to aid aerodynamic shape optimization (ASO), thanks to the availability of aerodynamic data and continued developments in deep learning. We review the applications of ML in ASO to date and pr...
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DOI: https://doi.org/10.1016/j.paerosci.2022.100849
José Padarian, Budiman Minasny, Alex B. McBratney • SOIL
(2020)
Abstract. The application of machine learning (ML) techniques in various fields of science has increased rapidly, especially in the last ten years. The increasing availability of soil data that can be efficiently acquired remotely and proxi...
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DOI: https://doi.org/10.5194/soil-6-35-2020
Andreas Müller, Sarah Guido (2016)
Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teac...
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Khalil A. Alruwaitee • Journal of Radiation Research and Applied Sciences
(2024)
Predictions on stock market prices are a noble task owing to huge complex, dynamic, and chaotic surroundings. Fast ups and downs arise in the stock market due to influences from foreign merchandise, such as sensitive political, stockholder,...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.jrras.2024.101172
Chirag Gupta, Venkategowda Ramegowda, Supratim Basu, Andy Pereira • Frontiers in Genetics
(2021)
Gene regulatory networks underpin stress response pathways in plants. However, parsing these networks to prioritize key genes underlying a particular trait is challenging. Here, we have built the Gene Regulation and Association Network (GRA...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fgene.2021.652189