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Academic Articles & Research Papers
Showing 20 of 1,656 academic articles
Simon Willcock, Javier Martínez‐López, Danny A. P. Hooftman, Kenneth J. Bagstad et al. • Ecosystem Services
(2018)
Recent developments in machine learning have expanded data-driven modelling (DDM) capabilities, allowing artificial intelligence to infer the behaviour of a system by computing and exploiting correlations between observed variables within i...
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DOI: https://doi.org/10.1016/j.ecoser.2018.04.004
Min-Hwa Choi, Woongchang Yoon • IEEE Access
(2025)
Port congestion and prolonged ship waiting times pose challenges for global trade and increase operational costs and inefficiencies. In this study, a novel machine learning-based predictive approach was proposed to improve port operations b...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3566429
Subrata Chakraborty, Biswajeet Pradhan • Sensors
(2024)
Machine learning (ML) models have experienced remarkable growth in their application for multimodal data analysis over the past decade [...]...
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Open Access (DOAJ)
DOI: 10.3390/s24092874
Jie Zhang, Zipeng Wang, Jinzheng Hu, Shihao Xiao et al. • Journal of Rock Mechanics and Geotechnical Engineering
(2022)
The data-driven phenomenological models based on deformation measurements have been widely utilized to predict the slope failure time (SFT). The observational and model uncertainties could lead the predicted SFT calculated from the phenomen...
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Open Access (DOAJ)
DOI: 10.1016/j.jrmge.2021.09.010
Shobhit K. Patel, Juveriya Parmar, Vijay Katkar, Fahad Ahmed Al-Zahrani et al. • Alexandria Engineering Journal
(2022)
The solar spectrum energy absorption is very important for designing any solar absorber. The need for absorbing visible, infrared, and ultraviolet regions is increasing as most of the absorbers absorb visible regions. We propose a metasurfa...
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Open Access (DOAJ)
DOI: 10.1016/j.aej.2022.03.080
Ziad F. Doughan, Sari S. Itani • IEEE Access
(2025)
This paper introduces Rectified Discriminatory Delta-Adjust (RDDA), a novel methodology that enhances interpolation-based predictive modeling through adaptive sensitivity parameters. Building upon the foundational Delta-Adjust algorithm, RD...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3641537
Marco Fiorucci, Marina Khoroshiltseva, Massimiliano Pontil, Arianna Traviglia et al. • Pattern Recognition Letters
(2020)
The application of Machine Learning (ML) to Cultural Heritage (CH) has evolved since basic statistical approaches such as Linear Regression to complex Deep Learning models. The question remains how much of this actively improves on the unde...
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DOI: https://doi.org/10.1016/j.patrec.2020.02.017
Yun Liu, Po-Hsuan Cameron Chen, Jonathan Krause, Lily H. Peng • JAMA
(2019)
In recent years, many new clinical diagnostic tools have been developed using complicated machine learning methods. Irrespective of how a diagnostic tool is derived, it must be evaluated using a 3-step process of deriving, validating, and e...
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DOI: https://doi.org/10.1001/jama.2019.16489
Matthias Seeger • International Journal of Neural Systems
(2004)
Gaussian processes (GPs) are natural generalisations of multivariate Gaussian random variables to infinite (countably or continuous) index sets. GPs have been applied in a large number of fields to a diverse range of ends, and very many dee...
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Open Access
DOI: https://doi.org/10.1142/s0129065704001899
Haoxin Mai, Tu C. Le, Dehong Chen, David Alan Winkler et al. • Chemical Reviews
(2022)
Electrocatalysts and photocatalysts are key to a sustainable future, generating clean fuels, reducing the impact of global warming, and providing solutions to environmental pollution. Improved processes for catalyst design and a better unde...
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DOI: https://doi.org/10.1021/acs.chemrev.2c00061
Khader Shameer, Kipp W. Johnson, Benjamin Scott Glicksberg, Joel T. Dudley et al. • Heart
(2018)
Artificial intelligence (AI) broadly refers to analytical algorithms that iteratively learn from data, allowing computers to find hidden insights without being explicitly programmed where to look. These include a family of operations encomp...
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DOI: https://doi.org/10.1136/heartjnl-2017-311198
Niloofar Asefi, Leonard Lupin-Jimenez, Tianning Wu, Ruoying He et al. • Machine Learning. Earth
(2025)
Reconstructing ocean dynamics from observational data is fundamentally limited by the sparse, irregular, and Lagrangian nature of spatial sampling, particularly in subsurface and remote regions. This sparsity poses significant challenges fo...
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Open Access (DOAJ)
DOI: 10.1088/3049-4753/ae0b70
Anwer Shees, Mohd Tariq, Arif I. Sarwat • Energies
(2024)
By integrating advanced technologies and data-driven systems in smart grids, there has been a significant revolution in the energy distribution sector, bringing a new era of efficiency and sustainability. Nevertheless, with this advancement...
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Open Access (DOAJ)
DOI: 10.3390/en17235870
Matthew Ryan, Jinjing Ye, Justin Sexton, Roslyn I. Hickson et al. • Royal Society Open Science
(2025)
Face mask wearing is a protective health behaviour that helps mitigate the spread of infectious diseases such as influenza and COVID-19. Understanding predictors of face mask wearing can help refine public health messaging and policy in fut...
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Open Access (DOAJ)
DOI: 10.1098/rsos.241941
Ikram Jennane, Yousef Farhaoui, Mohamed Khalifa Boutahir • Energies
(2026)
This study investigates multi-horizon forecasting of solar-based green hydrogen (H2) production in Southern Morocco (Dakhla: 23.7° N, 15.9° W; Laâyoune: 27.2° N, 13.2° W; and Guelmim: 29.0° N, 10.1° W) using daily meteorological time series...
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Open Access (DOAJ)
DOI: 10.3390/en19173984
Heming Jia, Marjan Kordani, Iman Ahmadianfar, Arvin Samadi Koucheksaraee et al. • Engineering Applications of Computational Fluid Mechanics
(2026)
Precise forecasting of water quality indices (WQI) is essential for safeguarding ecosystems, human health, and sustainable water resource management. This study presents an innovative approach for evaluating river Water Quality Indices usin...
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Open Access (DOAJ)
DOI: 10.1080/19942060.2025.2602582
Y. Y. Abdullahi, A. S. Nur, A. Sale • Journal of Applied Sciences and Environmental Management
(2025)
Machine learning provides more verbose algorithms capable of accurately predicting, classifying groups as needed. Consequently, the objective of this paper is to assess the benchmarking of Supervised Machine Learning Algorithms of K-Nearest...
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Open Access (DOAJ)
Sarah M. Alghamdi, Paul N. Schofield, Robert Hoehndorf • Disease Models & Mechanisms
(2022)
Computing phenotypic similarity helps identify new disease genes and diagnose rare diseases. Genotype–phenotype data from orthologous genes in model organisms can compensate for lack of human data and increase genome coverage. In the past d...
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Open Access (DOAJ)
DOI: 10.1242/dmm.049441
M. Graça Pereira, Martim Santos, Renata Magalhães, Cláudia Rodrigues et al. • Behavioral Sciences
(2025)
University students are at increased risk of developing burnout and psychological distress from high academic workloads and performance expectations. The purpose of this study is to analyze the relationship between psychological and lifesty...
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Open Access (DOAJ)
DOI: 10.3390/bs15040505
Mengnan Du, Ninghao Liu, Xia Hu • Communications of the ACM
(2019)
Uncovering the mysterious ways machine learning models make decisions....
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Open Access
DOI: https://doi.org/10.1145/3359786