Výsledky vyhledávání - "ANN (Artificial Neural Networks)"

Akademický článek

Multistage sugarcane yield prediction using machine learning algorithms

Autor: SHANKARAPPA SRIDHARA, SOUMYA B. R., GIRISH R. KASHYAP

Publikováno v: Journal of Agrometeorology, Vol 26, Iss 1 (2024)

Sugarcane is one of the leading commercial crops grown in India. The prevailing weather during the various crop-growth stages significantly impacts sugarcane productivity and the quality of its juice. The objective of this study was to predict the yi

Externí odkaz: https://doaj.org/article/f1baaec25b3b424c99444a884bb489d6

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Akademický článek

Monitor the Strength Status of Buildings Using Hybrid Machine Learning Technique

Autor: Vishnu Vardhana Rao M, Aparna Chaparala, Praphula Kumar Jain, Hanen Karamti, Walid Karamti

Publikováno v: IEEE Access, Vol 11, Pp 26441-26458 (2023)

Standard inspections of buildings are not always possible because of human flaws in prediction. Hence, we need more stable, scalable, and efficient automated processes. Structure Health Monitoring (SHM) is one of the automation systems for forecastin

Externí odkaz: https://doaj.org/article/4527b477dcb54c878330fda02f58bfc8

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Akademický článek

Data-Driven Prediction of Quartz Dissolution Rates at Near-Neutral and Alkaline Environments

Autor: Kai Gong, Tunahan Aytas, Shu Yang Zhang, Elsa A. Olivetti

Publikováno v: Frontiers in Materials, Vol 9 (2022)

Dissolution of silicate-based materials is important to many natural processes and engineering applications, including cement and concrete production. Here, we present a data-driven study to predict the dissolution rates of crystalline silica (i.e.,

Externí odkaz: https://doaj.org/article/1af60877b2834b2bbd0966ddf4753786

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Sensorless Speed Control of Synchronous Reluctance Motor Drives Based on Extended Kalman Filter and Neural Magnetic Model

Autor: DARIO PASQUALOTTO, Saverio Rigon, MAURO ZIGLIOTTO

Publikováno v: IEEE Transactions on Industrial Electronics. 70:1321-1330

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4f4282eb737776dfcf1e8b3b31f4aab2
https://doi.org/10.1109/tie.2022.3159962

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Akademický článek

Pedotransfer function for determining saturated hydraulic conductivity using Artificial Neural Network (ANN)

Autor: Edyta Kruk, Magdalena Malec, Sławomir Klatka, Andżelika Brodzińska-Cygan, Jan Kołodziej

Publikováno v: Acta Scientiarum Polonorum. Formatio Circumiectus, Vol 16, Iss 4, Pp 115-126 (2017)

In the work there were presented two pedotransfer models for determination of saturated hydraulic conductivity, generated by artificial neural networks (ANN). Models were learned based on empirical data obtained in laboratory, on 56 soil samples of d

Externí odkaz: https://doaj.org/article/8011e289c6e64c73b06b375512346031

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Machine learning applications in microbial ecology, human microbiome studies, and environmental monitoring

Autor: Stephen M. Techtmann, Ryan B. Ghannam

Publikováno v: Computational and Structural Biotechnology Journal, Vol 19, Iss, Pp 1092-1107 (2021)
Computational and Structural Biotechnology Journal

Graphical abstract
Advances in nucleic acid sequencing technology have enabled expansion of our ability to profile microbial diversity. These large datasets of taxonomic and functional diversity are key to better understanding microbial ecology.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e08600cfc4157ede957af097d02ed011
https://doi.org/10.1016/j.csbj.2021.01.028

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Artificial intelligence in clinical care amidst COVID-19 pandemic: A systematic review

Autor: Konstantina S. Nikita, Eleni S. Adamidi, Konstantinos Mitsis

Publikováno v: Computational and Structural Biotechnology Journal, Vol 19, Iss, Pp 2833-2850 (2021)
Computational and Structural Biotechnology Journal

Graphical abstract
The worldwide health crisis caused by the SARS-Cov-2 virus has resulted in>3 million deaths so far. Improving early screening, diagnosis and prognosis of the disease are critical steps in assisting healthcare professionals to

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::99d4904675baf780e5818934ae227323
http://www.sciencedirect.com/science/article/pii/S2001037021001914

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A review on machine learning approaches and trends in drug discovery

Autor: Victor Maojo, Nereida Rodriguez-Fernandez, Adrian Carballal, Carlos Fernandez-Lozano, Francisco J. Novoa, Alejandro Pazos, Paula Carracedo-Reboredo, Francisco Cedrón, Jose Liñares-Blanco

Publikováno v: Computational and Structural Biotechnology Journal, Vol 19, Iss, Pp 4538-4558 (2021)
RUC. Repositorio da Universidade da Coruña
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Computational and Structural Biotechnology Journal

Graphical abstract
Highlights • Machine Learning in drug discovery has greatly benefited the pharmaceutical industry. • Application of machine algorithms must entail a robust design in real clinical tasks. • Trending machine learning algor

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c1455b1a18d7c6c8d727e34d6b7d78f8
http://www.sciencedirect.com/science/article/pii/S2001037021003421

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Akademický článek

Signal prediction based on empirical mode decomposition and artificial neural networks

Autor: Wang Yong, Liu Yanping, Yang Jing

Publikováno v: Geodesy and Geodynamics, Vol 3, Iss 1, Pp 52-56 (2012)

In view of the usefulness of Empirical Mode Decomposition (EMD), Artificial Neural Networks (ANN), and Most Relevant Matching Extension (MRME) methods in dealing with nonlinear signals, we propose a new way of combining these methods to deal with sig

Externí odkaz: https://doaj.org/article/ea611390cedd470995c3766f2e8f53d6

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