摘要: Handbook of Research on Machine Learning Applications and Trends: Algorithms, Methods, and Techniques (9781605667669): Emilio Soria Olivas, José David Martín Guerrero, Marcelino Martinez-Sober, Jose Rafael Magdalena-Benedito, Antonio José Serrano López: Books...
Matrix factorisation and linear models have been the most popular ML algorithms, with around 1300 and 800 publications on these topics in 2020 respectively. In contrast, river researchers have had few applications in multiclass and multilabel algorithm, associate rule and Nave Bayes. The current ...
Numerical Simulation of Strength Limit of Surrounding Rock in Geotechnical Engineering Based on Machine Learning When the traditional method numerically simulates the strength of the surrounding rock, the error of obtaining the strength parameters is large, which lead... M Gu - IEEE International Confe...
There are comments on PubPeer for publication: Research on machine learning method and its application technology in intrusion information security detection (2020)
Machine Learning Applications in Sustainable Water Resource Management: A Systematic Review. In Emerging Technologies for Water Supply, Conservation and Management Springer Water; Springer: Cham, Switzerland, 2023; pp. 29–47. [Google Scholar] Mekanik, F.; Imteaz, M.A.; Gato-Trinidad, S.; El...
Explore advancements in state of the art machine learning research in speech and natural language, privacy, computer vision, health, and more.
1.Soori M, Arezoo B, Dastres R. Artificial intelligence, machine learning and deep learning in advanced robotics, a review.COGR. 2023;3:54-70.[DOI][Cited in This Article:1] 2.Sarker IH. Machine Learning: Algorithms, Real-World Applications and Research Directions.SN Comput Sci. 2021;2...
Machine Learning (ML) has been enjoying an unprecedented surge in applications that solve problems and enable automation in diverse domains. Primarily, this is due to the explosion in the availability of data, significant improvements in ML techniques, a
being compositional, sparse, and high-dimensional – necessitates special treatment. We then introduce traditional and novel methods and discuss their strengths and applications. Finally, we discuss the outlook of machine and deep learning pipelines, focusing on bottlenecks and considerations to address ...
To provide a comprehensive view on machine learning algorithms that can be applied to enhance the intelligence and capabilities of a data-driven application. To discuss the applicability of machine learning-based solutions in various real-world application domains. ...